Context Navigation

CbcNode.cpp @ 2182

Last change on this file since 2182 was 2182, checked in by forrest, 6 years ago
fix bug showing up in proximity search
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 249.3 KB

Line
1	/* $Id: CbcNode.cpp 2182 2015-04-14 10:36:07Z forrest $ */
2	// Copyright (C) 2002, International Business Machines
3	// Corporation and others. All Rights Reserved.
4	// This code is licensed under the terms of the Eclipse Public License (EPL).
5
6	#if defined(_MSC_VER)
7	// Turn off compiler warning about long names
8	# pragma warning(disable:4786)
9	#include <windows.h> // for Sleep()
10	#ifdef small
11	#undef small
12	#endif
13	#else
14	#include <unistd.h> // for usleep()
15	#endif
16
17	#include "CbcConfig.h"
18	#ifdef COIN_HAS_NTY
19	#include "CbcSymmetry.hpp"
20	#endif
21	//#define DEBUG_SOLUTION
22	#ifdef DEBUG_SOLUTION
23	#define COIN_DETAIL
24	#endif
25	#include <string>
26	//#define CBC_DEBUG 1
27	//#define CHECK_CUT_COUNTS
28	//#define CHECK_NODE
29	//#define CBC_CHECK_BASIS
30	#include <cassert>
31	#include <cfloat>
32	#define CUTS
33	#include "OsiSolverInterface.hpp"
34	#include "OsiChooseVariable.hpp"
35	#include "OsiAuxInfo.hpp"
36	#include "OsiSolverBranch.hpp"
37	#include "CoinWarmStartBasis.hpp"
38	#include "CoinTime.hpp"
39	#include "CbcModel.hpp"
40	#include "CbcNode.hpp"
41	#include "CbcStatistics.hpp"
42	#include "CbcStrategy.hpp"
43	#include "CbcBranchActual.hpp"
44	#include "CbcBranchDynamic.hpp"
45	#include "OsiRowCut.hpp"
46	#include "OsiRowCutDebugger.hpp"
47	#include "OsiCuts.hpp"
48	#include "CbcCountRowCut.hpp"
49	#include "CbcFeasibilityBase.hpp"
50	#include "CbcMessage.hpp"
51	#ifdef COIN_HAS_CLP
52	#include "OsiClpSolverInterface.hpp"
53	#include "ClpSimplexOther.hpp"
54	#include "ClpSolve.hpp"
55	#include "ClpDualRowSteepest.hpp"
56	#include "ClpPrimalColumnPivot.hpp"
57	#endif
58	using namespace std;
59	#include "CglCutGenerator.hpp"
60
61
62	CbcNode::CbcNode() :
63	nodeInfo_(NULL),
64	objectiveValue_(1.0e100),
65	guessedObjectiveValue_(1.0e100),
66	sumInfeasibilities_(0.0),
67	branch_(NULL),
68	depth_(-1),
69	numberUnsatisfied_(0),
70	nodeNumber_(-1),
71	state_(0)
72	{
73	#ifdef CHECK_NODE
74	printf("CbcNode %p Constructor\n", this);
75	#endif
76	}
77	// Print
78	void
79	CbcNode::print() const
80	{
81	printf("number %d obj %g depth %d sumun %g nunsat %d state %d\n",
82	nodeNumber_, objectiveValue_, depth_, sumInfeasibilities_, numberUnsatisfied_, state_);
83	}
84	CbcNode::CbcNode(CbcModel * model,
85	CbcNode * lastNode) :
86	nodeInfo_(NULL),
87	objectiveValue_(1.0e100),
88	guessedObjectiveValue_(1.0e100),
89	sumInfeasibilities_(0.0),
90	branch_(NULL),
91	depth_(-1),
92	numberUnsatisfied_(0),
93	nodeNumber_(-1),
94	state_(0)
95	{
96	#ifdef CHECK_NODE
97	printf("CbcNode %p Constructor from model\n", this);
98	#endif
99	model->setObjectiveValue(this, lastNode);
100
101	if (lastNode) {
102	if (lastNode->nodeInfo_) {
103	lastNode->nodeInfo_->increment();
104	}
105	}
106	nodeNumber_ = model->getNodeCount();
107	}
108
109	#define CBC_NEW_CREATEINFO
110	#ifdef CBC_NEW_CREATEINFO
111
112	/*
113	New createInfo, with basis manipulation hidden inside mergeBasis. Allows
114	solvers to override and carry over all information from one basis to
115	another.
116	*/
117
118	void
119	CbcNode::createInfo (CbcModel *model,
120	CbcNode *lastNode,
121	const CoinWarmStartBasis *lastws,
122	const double lastLower, const double lastUpper,
123	int numberOldActiveCuts, int numberNewCuts)
124
125	{
126	OsiSolverInterface *solver = model->solver();
127	CbcStrategy *strategy = model->strategy();
128	/*
129	The root --- no parent. Create full basis and bounds information.
130	*/
131	if (!lastNode) {
132	if (!strategy)
133	nodeInfo_ = new CbcFullNodeInfo(model, solver->getNumRows());
134	else
135	nodeInfo_ = strategy->fullNodeInfo(model, solver->getNumRows());
136	} else {
137	/*
138	Not the root. Create an edit from the parent's basis & bound information.
139	This is not quite as straightforward as it seems. We need to reintroduce
140	cuts we may have dropped out of the basis, in the correct position, because
141	this whole process is strictly positional. Start by grabbing the current
142	basis.
143	*/
144	bool mustDeleteBasis;
145	const CoinWarmStartBasis *ws =
146	dynamic_cast<const CoinWarmStartBasis*>(solver->getPointerToWarmStart(mustDeleteBasis));
147	assert(ws != NULL); // make sure not volume
148	//int numberArtificials = lastws->getNumArtificial();
149	int numberColumns = solver->getNumCols();
150	int numberRowsAtContinuous = model->numberRowsAtContinuous();
151	int currentNumberCuts = model->currentNumberCuts();
152	# ifdef CBC_CHECK_BASIS
153	std::cout
154	<< "Before expansion: orig " << numberRowsAtContinuous
155	<< ", old " << numberOldActiveCuts
156	<< ", new " << numberNewCuts
157	<< ", current " << currentNumberCuts << "." << std::endl ;
158	ws->print();
159	# endif
160	/*
161	Clone the basis and resize it to hold the structural constraints, plus
162	all the cuts: old cuts, both active and inactive (currentNumberCuts),
163	and new cuts (numberNewCuts). This will become the expanded basis.
164	*/
165	CoinWarmStartBasis *expanded =
166	dynamic_cast<CoinWarmStartBasis *>(ws->clone()) ;
167	int iCompact = numberRowsAtContinuous + numberOldActiveCuts + numberNewCuts ;
168	// int nPartial = numberRowsAtContinuous+currentNumberCuts;
169	int iFull = numberRowsAtContinuous + currentNumberCuts + numberNewCuts;
170	// int maxBasisLength = ((iFull+15)>>4)+((numberColumns+15)>>4);
171	// printf("l %d full %d\n",maxBasisLength,iFull);
172	expanded->resize(iFull, numberColumns);
173	# ifdef CBC_CHECK_BASIS
174	std::cout
175	<< "\tFull basis " << iFull << " rows, "
176	<< numberColumns << " columns; compact "
177	<< iCompact << " rows." << std::endl ;
178	# endif
179	/*
180	Now flesh out the expanded basis. The clone already has the
181	correct status information for the variables and for the structural
182	(numberRowsAtContinuous) constraints. Any indices beyond nPartial must be
183	cuts created while processing this node --- they can be copied en bloc
184	into the correct position in the expanded basis. The space reserved for
185	xferRows is a gross overestimate.
186	*/
187	CoinWarmStartBasis::XferVec xferRows ;
188	xferRows.reserve(iFull - numberRowsAtContinuous + 1) ;
189	if (numberNewCuts) {
190	xferRows.push_back(
191	CoinWarmStartBasis::XferEntry(iCompact - numberNewCuts,
192	iFull - numberNewCuts, numberNewCuts)) ;
193	}
194	/*
195	From nPartial down, record the entries we want to copy from the current
196	basis (the entries for the active cuts; non-zero in the list returned
197	by addedCuts). Fill the expanded basis with entries showing a status of
198	basic for the deactivated (loose) cuts.
199	*/
200	CbcCountRowCut **cut = model->addedCuts();
201	iFull -= (numberNewCuts + 1) ;
202	iCompact -= (numberNewCuts + 1) ;
203	int runLen = 0 ;
204	CoinWarmStartBasis::XferEntry entry(-1, -1, -1) ;
205	while (iFull >= numberRowsAtContinuous) {
206	for ( ; iFull >= numberRowsAtContinuous &&
207	cut[iFull-numberRowsAtContinuous] ; iFull--)
208	runLen++ ;
209	if (runLen) {
210	iCompact -= runLen ;
211	entry.first = iCompact + 1 ;
212	entry.second = iFull + 1 ;
213	entry.third = runLen ;
214	runLen = 0 ;
215	xferRows.push_back(entry) ;
216	}
217	for ( ; iFull >= numberRowsAtContinuous &&
218	!cut[iFull-numberRowsAtContinuous] ; iFull--)
219	expanded->setArtifStatus(iFull, CoinWarmStartBasis::basic);
220	}
221	/*
222	Finally, call mergeBasis to copy over entries from the current basis to
223	the expanded basis. Since we cloned the expanded basis from the active basis
224	and haven't changed the number of variables, only row status entries need
225	to be copied.
226	*/
227	expanded->mergeBasis(ws, &xferRows, 0) ;
228
229	#ifdef CBC_CHECK_BASIS
230	std::cout << "Expanded basis:" << std::endl ;
231	expanded->print() ;
232	std::cout << "Diffing against:" << std::endl ;
233	lastws->print() ;
234	#endif
235	assert (expanded->getNumArtificial() >= lastws->getNumArtificial());
236	#ifdef CLP_INVESTIGATE
237	if (!expanded->fullBasis()) {
238	int iFull = numberRowsAtContinuous + currentNumberCuts + numberNewCuts;
239	printf("cont %d old %d new %d current %d full inc %d full %d\n",
240	numberRowsAtContinuous, numberOldActiveCuts, numberNewCuts,
241	currentNumberCuts, iFull, iFull - numberNewCuts);
242	}
243	#endif
244
245	/*
246	Now that we have two bases in proper positional correspondence, creating
247	the actual diff is dead easy.
248
249	Note that we're going to compare the expanded basis here to the stripped
250	basis (lastws) produced by addCuts. It doesn't affect the correctness (the
251	diff process has no knowledge of the meaning of an entry) but it does
252	mean that we'll always generate a whack of diff entries because the expanded
253	basis is considerably larger than the stripped basis.
254	*/
255	CoinWarmStartDiff *basisDiff = expanded->generateDiff(lastws) ;
256
257	/*
258	Diff the bound vectors. It's assumed the number of structural variables
259	is not changing. For branching objects that change bounds on integer
260	variables, we should see at least one bound change as a consequence
261	of applying the branch that generated this subproblem from its parent.
262	This need not hold for other types of branching objects (hyperplane
263	branches, for example).
264	*/
265	const double * lower = solver->getColLower();
266	const double * upper = solver->getColUpper();
267
268	double boundChanges = new double [2numberColumns] ;
269	int variables = new int [2numberColumns] ;
270	int numberChangedBounds = 0;
271
272	int i;
273	for (i = 0; i < numberColumns; i++) {
274	if (lower[i] != lastLower[i]) {
275	variables[numberChangedBounds] = i;
276	boundChanges[numberChangedBounds++] = lower[i];
277	}
278	if (upper[i] != lastUpper[i]) {
279	variables[numberChangedBounds] = i \| 0x80000000;
280	boundChanges[numberChangedBounds++] = upper[i];
281	}
282	#ifdef CBC_DEBUG
283	if (lower[i] != lastLower[i]) {
284	std::cout
285	<< "lower on " << i << " changed from "
286	<< lastLower[i] << " to " << lower[i] << std::endl ;
287	}
288	if (upper[i] != lastUpper[i]) {
289	std::cout
290	<< "upper on " << i << " changed from "
291	<< lastUpper[i] << " to " << upper[i] << std::endl ;
292	}
293	#endif
294	}
295	#ifdef CBC_DEBUG
296	std::cout << numberChangedBounds << " changed bounds." << std::endl ;
297	#endif
298	//if (lastNode->branchingObject()->boundBranch())
299	//assert (numberChangedBounds);
300	/*
301	Hand the lot over to the CbcPartialNodeInfo constructor, then clean up and
302	return.
303	*/
304	if (!strategy)
305	nodeInfo_ =
306	new CbcPartialNodeInfo(lastNode->nodeInfo_, this, numberChangedBounds,
307	variables, boundChanges, basisDiff) ;
308	else
309	nodeInfo_ =
310	strategy->partialNodeInfo(model, lastNode->nodeInfo_, this,
311	numberChangedBounds, variables, boundChanges,
312	basisDiff) ;
313	delete basisDiff ;
314	delete [] boundChanges;
315	delete [] variables;
316	delete expanded ;
317	if (mustDeleteBasis)
318	delete ws;
319	}
320	// Set node number
321	nodeInfo_->setNodeNumber(model->getNodeCount2());
322	state_ \|= 2; // say active
323	}
324
325	#else // CBC_NEW_CREATEINFO
326
327	/*
328	Original createInfo, with bare manipulation of basis vectors. Fails if solver
329	maintains additional information in basis.
330	*/
331
332	void
333	CbcNode::createInfo (CbcModel *model,
334	CbcNode *lastNode,
335	const CoinWarmStartBasis *lastws,
336	const double lastLower, const double lastUpper,
337	int numberOldActiveCuts, int numberNewCuts)
338	{
339	OsiSolverInterface * solver = model->solver();
340	CbcStrategy * strategy = model->strategy();
341	/*
342	The root --- no parent. Create full basis and bounds information.
343	*/
344	if (!lastNode) {
345	if (!strategy)
346	nodeInfo_ = new CbcFullNodeInfo(model, solver->getNumRows());
347	else
348	nodeInfo_ = strategy->fullNodeInfo(model, solver->getNumRows());
349	}
350	/*
351	Not the root. Create an edit from the parent's basis & bound information.
352	This is not quite as straightforward as it seems. We need to reintroduce
353	cuts we may have dropped out of the basis, in the correct position, because
354	this whole process is strictly positional. Start by grabbing the current
355	basis.
356	*/
357	else {
358	bool mustDeleteBasis;
359	const CoinWarmStartBasis* ws =
360	dynamic_cast<const CoinWarmStartBasis*>(solver->getPointerToWarmStart(mustDeleteBasis));
361	assert(ws != NULL); // make sure not volume
362	//int numberArtificials = lastws->getNumArtificial();
363	int numberColumns = solver->getNumCols();
364
365	const double * lower = solver->getColLower();
366	const double * upper = solver->getColUpper();
367
368	int i;
369	/*
370	Create a clone and resize it to hold all the structural constraints, plus
371	all the cuts: old cuts, both active and inactive (currentNumberCuts), and
372	new cuts (numberNewCuts).
373
374	TODO: You'd think that the set of constraints (logicals) in the expanded
375	basis should match the set represented in lastws. At least, that's
376	what I thought. But at the point I first looked hard at this bit of
377	code, it turned out that lastws was the stripped basis produced at
378	the end of addCuts(), rather than the raw basis handed back by
379	addCuts1(). The expanded basis here is equivalent to the raw basis of
380	addCuts1(). I said ``whoa, that's not good, I must have introduced a
381	bug'' and went back to John's code to see where I'd gone wrong.
382	And discovered the same `error' in his code.
383
384	After a bit of thought, my conclusion is that correctness is not
385	affected by whether lastws is the stripped or raw basis. The diffs
386	have no semantics --- just a set of changes that need to be made
387	to convert lastws into expanded. I think the only effect is that we
388	store a lot more diffs (everything in expanded that's not covered by
389	the stripped basis). But I need to give this more thought. There
390	may well be some subtle error cases.
391
392	In the mean time, I've twiddled addCuts() to set lastws to the raw
393	basis. Makes me (Lou) less nervous to compare apples to apples.
394	*/
395	CoinWarmStartBasis *expanded =
396	dynamic_cast<CoinWarmStartBasis *>(ws->clone()) ;
397	int numberRowsAtContinuous = model->numberRowsAtContinuous();
398	int iFull = numberRowsAtContinuous + model->currentNumberCuts() +
399	numberNewCuts;
400	//int numberArtificialsNow = iFull;
401	//int maxBasisLength = ((iFull+15)>>4)+((numberColumns+15)>>4);
402	//printf("l %d full %d\n",maxBasisLength,iFull);
403	if (expanded)
404	expanded->resize(iFull, numberColumns);
405	#ifdef CBC_CHECK_BASIS
406	printf("Before expansion: orig %d, old %d, new %d, current %d\n",
407	numberRowsAtContinuous, numberOldActiveCuts, numberNewCuts,
408	model->currentNumberCuts()) ;
409	ws->print();
410	#endif
411	/*
412	Now fill in the expanded basis. Any indices beyond nPartial must
413	be cuts created while processing this node --- they can be copied directly
414	into the expanded basis. From nPartial down, pull the status of active cuts
415	from ws, interleaving with a B entry for the deactivated (loose) cuts.
416	*/
417	int numberDropped = model->currentNumberCuts() - numberOldActiveCuts;
418	int iCompact = iFull - numberDropped;
419	CbcCountRowCut ** cut = model->addedCuts();
420	int nPartial = model->currentNumberCuts() + numberRowsAtContinuous;
421	iFull--;
422	for (; iFull >= nPartial; iFull--) {
423	CoinWarmStartBasis::Status status = ws->getArtifStatus(--iCompact);
424	//assert (status != CoinWarmStartBasis::basic); // may be permanent cut
425	expanded->setArtifStatus(iFull, status);
426	}
427	for (; iFull >= numberRowsAtContinuous; iFull--) {
428	if (cut[iFull-numberRowsAtContinuous]) {
429	CoinWarmStartBasis::Status status = ws->getArtifStatus(--iCompact);
430	// If no cut generator being used then we may have basic variables
431	//if (model->getMaximumCutPasses()&&
432	// status == CoinWarmStartBasis::basic)
433	//printf("cut basic\n");
434	expanded->setArtifStatus(iFull, status);
435	} else {
436	expanded->setArtifStatus(iFull, CoinWarmStartBasis::basic);
437	}
438	}
439	#ifdef CBC_CHECK_BASIS
440	printf("Expanded basis\n");
441	expanded->print() ;
442	printf("Diffing against\n") ;
443	lastws->print() ;
444	#endif
445	/*
446	Now that we have two bases in proper positional correspondence, creating
447	the actual diff is dead easy.
448	*/
449
450	CoinWarmStartDiff *basisDiff = expanded->generateDiff(lastws) ;
451	/*
452	Diff the bound vectors. It's assumed the number of structural variables is
453	not changing. Assuming that branching objects all involve integer variables,
454	we should see at least one bound change as a consequence of processing this
455	subproblem. Different types of branching objects could break this assertion.
456	Not true at all - we have not applied current branch - JJF.
457	*/
458	double boundChanges = new double [2numberColumns] ;
459	int variables = new int [2numberColumns] ;
460	int numberChangedBounds = 0;
461	for (i = 0; i < numberColumns; i++) {
462	if (lower[i] != lastLower[i]) {
463	variables[numberChangedBounds] = i;
464	boundChanges[numberChangedBounds++] = lower[i];
465	}
466	if (upper[i] != lastUpper[i]) {
467	variables[numberChangedBounds] = i \| 0x80000000;
468	boundChanges[numberChangedBounds++] = upper[i];
469	}
470	#ifdef CBC_DEBUG
471	if (lower[i] != lastLower[i])
472	printf("lower on %d changed from %g to %g\n",
473	i, lastLower[i], lower[i]);
474	if (upper[i] != lastUpper[i])
475	printf("upper on %d changed from %g to %g\n",
476	i, lastUpper[i], upper[i]);
477	#endif
478	}
479	#ifdef CBC_DEBUG
480	printf("%d changed bounds\n", numberChangedBounds) ;
481	#endif
482	//if (lastNode->branchingObject()->boundBranch())
483	//assert (numberChangedBounds);
484	/*
485	Hand the lot over to the CbcPartialNodeInfo constructor, then clean up and
486	return.
487	*/
488	if (!strategy)
489	nodeInfo_ =
490	new CbcPartialNodeInfo(lastNode->nodeInfo_, this, numberChangedBounds,
491	variables, boundChanges, basisDiff) ;
492	else
493	nodeInfo_ = strategy->partialNodeInfo(model, lastNode->nodeInfo_, this, numberChangedBounds,
494	variables, boundChanges, basisDiff) ;
495	delete basisDiff ;
496	delete [] boundChanges;
497	delete [] variables;
498	delete expanded ;
499	if (mustDeleteBasis)
500	delete ws;
501	}
502	// Set node number
503	nodeInfo_->setNodeNumber(model->getNodeCount2());
504	state_ \|= 2; // say active
505	}
506
507	#endif // CBC_NEW_CREATEINFO
508	/*
509	The routine scans through the object list of the model looking for objects
510	that indicate infeasibility. It tests each object using strong branching
511	and selects the one with the least objective degradation. A corresponding
512	branching object is left attached to lastNode.
513
514	If strong branching is disabled, a candidate object is chosen essentially
515	at random (whatever object ends up in pos'n 0 of the candidate array).
516
517	If a branching candidate is found to be monotone, bounds are set to fix the
518	variable and the routine immediately returns (the caller is expected to
519	reoptimize).
520
521	If a branching candidate is found to result in infeasibility in both
522	directions, the routine immediately returns an indication of infeasibility.
523
524	Returns: 0 both branch directions are feasible
525	-1 branching variable is monotone
526	-2 infeasible
527
528	Original comments:
529	Here could go cuts etc etc
530	For now just fix on objective from strong branching.
531	*/
532
533	int CbcNode::chooseBranch (CbcModel model, CbcNode lastNode, int numberPassesLeft)
534
535	{
536	if (lastNode)
537	depth_ = lastNode->depth_ + 1;
538	else
539	depth_ = 0;
540	delete branch_;
541	branch_ = NULL;
542	OsiSolverInterface * solver = model->solver();
543	# ifdef COIN_HAS_CLP
544	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
545	int saveClpOptions = 0;
546	if (osiclp) {
547	// for faster hot start
548	saveClpOptions = osiclp->specialOptions();
549	osiclp->setSpecialOptions(saveClpOptions \| 8192);
550	}
551	# else
552	OsiSolverInterface *osiclp = NULL ;
553	# endif
554	double saveObjectiveValue = solver->getObjValue();
555	double objectiveValue = CoinMax(solver->getObjSense() * saveObjectiveValue, objectiveValue_);
556	const double * lower = solver->getColLower();
557	const double * upper = solver->getColUpper();
558	// See what user thinks
559	int anyAction = model->problemFeasibility()->feasible(model, 0);
560	if (anyAction) {
561	// will return -2 if infeasible , 0 if treat as integer
562	return anyAction - 1;
563	}
564	double integerTolerance =
565	model->getDblParam(CbcModel::CbcIntegerTolerance);
566	// point to useful information
567	OsiBranchingInformation usefulInfo = model->usefulInformation();
568	// and modify
569	usefulInfo.depth_ = depth_;
570	int i;
571	bool beforeSolution = model->getSolutionCount() == 0;
572	int numberStrong = model->numberStrong();
573	// switch off strong if hotstart
574	const double * hotstartSolution = model->hotstartSolution();
575	const int * hotstartPriorities = model->hotstartPriorities();
576	int numberObjects = model->numberObjects();
577	int numberColumns = model->getNumCols();
578	double * saveUpper = new double[numberColumns];
579	double * saveLower = new double[numberColumns];
580	for (i = 0; i < numberColumns; i++) {
581	saveLower[i] = lower[i];
582	saveUpper[i] = upper[i];
583	}
584
585	// Save solution in case heuristics need good solution later
586
587	double * saveSolution = new double[numberColumns];
588	memcpy(saveSolution, solver->getColSolution(), numberColumns*sizeof(double));
589	model->reserveCurrentSolution(saveSolution);
590	if (hotstartSolution) {
591	numberStrong = 0;
592	if ((model->moreSpecialOptions()&1024) != 0) {
593	int nBad = 0;
594	int nUnsat = 0;
595	int nDiff = 0;
596	for (int i = 0; i < numberObjects; i++) {
597	OsiObject * object = model->modifiableObject(i);
598	const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object);
599	if (thisOne) {
600	int iColumn = thisOne->columnNumber();
601	double targetValue = hotstartSolution[iColumn];
602	double value = saveSolution[iColumn];
603	if (fabs(value - floor(value + 0.5)) > 1.0e-6) {
604	nUnsat++;
605	#ifdef CLP_INVESTIGATE
606	printf("H %d is %g target %g\n", iColumn, value, targetValue);
607	#endif
608	} else if (fabs(targetValue - value) > 1.0e-6) {
609	nDiff++;
610	}
611	if (targetValue < saveLower[iColumn] \|\|
612	targetValue > saveUpper[iColumn]) {
613	#ifdef CLP_INVESTIGATE
614	printf("%d has target %g and current bounds %g and %g\n",
615	iColumn, targetValue, saveLower[iColumn], saveUpper[iColumn]);
616	#endif
617	nBad++;
618	}
619	}
620	}
621	#ifdef CLP_INVESTIGATE
622	printf("Hot %d unsatisfied, %d outside limits, %d different\n",
623	nUnsat, nBad, nDiff);
624	#endif
625	if (nBad) {
626	// switch off as not possible
627	hotstartSolution = NULL;
628	model->setHotstartSolution(NULL, NULL);
629	usefulInfo.hotstartSolution_ = NULL;
630	}
631	}
632	}
633	int numberStrongDone = 0;
634	int numberUnfinished = 0;
635	int numberStrongInfeasible = 0;
636	int numberStrongIterations = 0;
637	int saveNumberStrong = numberStrong;
638	bool checkFeasibility = numberObjects > model->numberIntegers();
639	int maximumStrong = CoinMax(CoinMin(numberStrong, numberObjects), 1);
640	/*
641	Get a branching decision object. Use the default decision criteria unless
642	the user has loaded a decision method into the model.
643	*/
644	CbcBranchDecision *decision = model->branchingMethod();
645	CbcDynamicPseudoCostBranchingObject * dynamicBranchingObject =
646	dynamic_cast<CbcDynamicPseudoCostBranchingObject *>(decision);
647	if (!decision \|\| dynamicBranchingObject)
648	decision = new CbcBranchDefaultDecision();
649	decision->initialize(model);
650	CbcStrongInfo * choice = new CbcStrongInfo[maximumStrong];
651	// May go round twice if strong branching fixes all local candidates
652	bool finished = false;
653	double estimatedDegradation = 0.0;
654	while (!finished) {
655	finished = true;
656	// Some objects may compute an estimate of best solution from here
657	estimatedDegradation = 0.0;
658	//int numberIntegerInfeasibilities=0; // without odd ones
659	numberStrongDone = 0;
660	numberUnfinished = 0;
661	numberStrongInfeasible = 0;
662	numberStrongIterations = 0;
663
664	// We may go round this loop twice (only if we think we have solution)
665	for (int iPass = 0; iPass < 2; iPass++) {
666
667	// compute current state
668	//int numberObjectInfeasibilities; // just odd ones
669	//model->feasibleSolution(
670	// numberIntegerInfeasibilities,
671	// numberObjectInfeasibilities);
672	// Some objects may compute an estimate of best solution from here
673	estimatedDegradation = 0.0;
674	numberUnsatisfied_ = 0;
675	// initialize sum of "infeasibilities"
676	sumInfeasibilities_ = 0.0;
677	int bestPriority = COIN_INT_MAX;
678	/*
679	Scan for branching objects that indicate infeasibility. Choose the best
680	maximumStrong candidates, using priority as the first criteria, then
681	integer infeasibility.
682
683	The algorithm is to fill the choice array with a set of good candidates (by
684	infeasibility) with priority bestPriority. Finding a candidate with
685	priority better (less) than bestPriority flushes the choice array. (This
686	serves as initialization when the first candidate is found.)
687
688	A new candidate is added to choices only if its infeasibility exceeds the
689	current max infeasibility (mostAway). When a candidate is added, it
690	replaces the candidate with the smallest infeasibility (tracked by
691	iSmallest).
692	*/
693	int iSmallest = 0;
694	double mostAway = 1.0e-100;
695	for (i = 0 ; i < maximumStrong ; i++)
696	choice[i].possibleBranch = NULL ;
697	numberStrong = 0;
698	bool canDoOneHot = false;
699	for (i = 0; i < numberObjects; i++) {
700	OsiObject * object = model->modifiableObject(i);
701	int preferredWay;
702	double infeasibility = object->infeasibility(&usefulInfo, preferredWay);
703	int priorityLevel = object->priority();
704	if (hotstartSolution) {
705	// we are doing hot start
706	const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object);
707	if (thisOne) {
708	int iColumn = thisOne->columnNumber();
709	bool canDoThisHot = true;
710	double targetValue = hotstartSolution[iColumn];
711	if (saveUpper[iColumn] > saveLower[iColumn]) {
712	double value = saveSolution[iColumn];
713	// clean
714	value = CoinMin(value,saveUpper[iColumn]);
715	value = CoinMax(value,saveLower[iColumn]);
716	if (hotstartPriorities)
717	priorityLevel = hotstartPriorities[iColumn];
718	//double originalLower = thisOne->originalLower();
719	//double originalUpper = thisOne->originalUpper();
720	// switch off if not possible
721	if (targetValue >= saveLower[iColumn] && targetValue <= saveUpper[iColumn]) {
722	/* priority outranks rest always if negative
723	otherwise can be downgraded if at correct level.
724	Infeasibility may be increased to choose 1.0 values first.
725	choose one near wanted value
726	*/
727	if (fabs(value - targetValue) > integerTolerance) {
728	//if (infeasibility>0.01)
729	//infeasibility = fabs(1.0e6-fabs(value-targetValue));
730	//else
731	infeasibility = fabs(value - targetValue);
732	//if (targetValue==1.0)
733	//infeasibility += 1.0;
734	if (value > targetValue) {
735	preferredWay = -1;
736	} else {
737	preferredWay = 1;
738	}
739	priorityLevel = CoinAbs(priorityLevel);
740	} else if (priorityLevel < 0) {
741	priorityLevel = CoinAbs(priorityLevel);
742	if (targetValue == saveLower[iColumn]) {
743	infeasibility = integerTolerance + 1.0e-12;
744	preferredWay = -1;
745	} else if (targetValue == saveUpper[iColumn]) {
746	infeasibility = integerTolerance + 1.0e-12;
747	preferredWay = 1;
748	} else {
749	// can't
750	priorityLevel += 10000000;
751	canDoThisHot = false;
752	}
753	} else {
754	priorityLevel += 10000000;
755	canDoThisHot = false;
756	}
757	} else {
758	// switch off if not possible
759	canDoThisHot = false;
760	}
761	if (canDoThisHot)
762	canDoOneHot = true;
763	} else if (targetValue < saveLower[iColumn] \|\| targetValue > saveUpper[iColumn]) {
764	}
765	} else {
766	priorityLevel += 10000000;
767	}
768	}
769	if (infeasibility) {
770	// Increase estimated degradation to solution
771	estimatedDegradation += CoinMin(object->upEstimate(), object->downEstimate());
772	numberUnsatisfied_++;
773	sumInfeasibilities_ += infeasibility;
774	// Better priority? Flush choices.
775	if (priorityLevel < bestPriority) {
776	int j;
777	iSmallest = 0;
778	for (j = 0; j < maximumStrong; j++) {
779	choice[j].upMovement = 0.0;
780	delete choice[j].possibleBranch;
781	choice[j].possibleBranch = NULL;
782	}
783	bestPriority = priorityLevel;
784	mostAway = 1.0e-100;
785	numberStrong = 0;
786	} else if (priorityLevel > bestPriority) {
787	continue;
788	}
789	// Check for suitability based on infeasibility.
790	if (infeasibility > mostAway) {
791	//add to list
792	choice[iSmallest].upMovement = infeasibility;
793	delete choice[iSmallest].possibleBranch;
794	CbcObject * obj =
795	dynamic_cast <CbcObject *>(object) ;
796	assert (obj);
797	choice[iSmallest].possibleBranch = obj->createCbcBranch(solver, &usefulInfo, preferredWay);
798	numberStrong = CoinMax(numberStrong, iSmallest + 1);
799	// Save which object it was
800	choice[iSmallest].objectNumber = i;
801	int j;
802	iSmallest = -1;
803	mostAway = 1.0e50;
804	for (j = 0; j < maximumStrong; j++) {
805	if (choice[j].upMovement < mostAway) {
806	mostAway = choice[j].upMovement;
807	iSmallest = j;
808	}
809	}
810	}
811	}
812	}
813	if (!canDoOneHot && hotstartSolution) {
814	// switch off as not possible
815	hotstartSolution = NULL;
816	model->setHotstartSolution(NULL, NULL);
817	usefulInfo.hotstartSolution_ = NULL;
818	}
819	if (numberUnsatisfied_) {
820	// some infeasibilities - go to next steps
821	#ifdef CLP_INVESTIGATE
822	if (hotstartSolution) {
823	int k = choice[0].objectNumber;
824	OsiObject * object = model->modifiableObject(k);
825	const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object);
826	assert (thisOne);
827	int iColumn = thisOne->columnNumber();
828	double targetValue = hotstartSolution[iColumn];
829	double value = saveSolution[iColumn];
830	printf("Branch on %d has target %g (value %g) and current bounds %g and %g\n",
831	iColumn, targetValue, value, saveLower[iColumn], saveUpper[iColumn]);
832	}
833	#endif
834	break;
835	} else if (!iPass) {
836	// looks like a solution - get paranoid
837	bool roundAgain = false;
838	// get basis
839	CoinWarmStartBasis * ws = dynamic_cast<CoinWarmStartBasis*>(solver->getWarmStart());
840	if (!ws)
841	break;
842	for (i = 0; i < numberColumns; i++) {
843	double value = saveSolution[i];
844	if (value < lower[i]) {
845	saveSolution[i] = lower[i];
846	roundAgain = true;
847	ws->setStructStatus(i, CoinWarmStartBasis::atLowerBound);
848	} else if (value > upper[i]) {
849	saveSolution[i] = upper[i];
850	roundAgain = true;
851	ws->setStructStatus(i, CoinWarmStartBasis::atUpperBound);
852	}
853	}
854	if (roundAgain && saveNumberStrong) {
855	// restore basis
856	solver->setWarmStart(ws);
857	delete ws;
858	solver->resolve();
859	memcpy(saveSolution, solver->getColSolution(), numberColumns*sizeof(double));
860	model->reserveCurrentSolution(saveSolution);
861	if (!solver->isProvenOptimal()) {
862	// infeasible
863	anyAction = -2;
864	break;
865	}
866	} else {
867	delete ws;
868	break;
869	}
870	}
871	}
872	/* Some solvers can do the strong branching calculations faster if
873	they do them all at once. At present only Clp does for ordinary
874	integers but I think this coding would be easy to modify
875	*/
876	bool allNormal = true; // to say if we can do fast strong branching
877	// Say which one will be best
878	int bestChoice = 0;
879	double worstInfeasibility = 0.0;
880	for (i = 0; i < numberStrong; i++) {
881	choice[i].numIntInfeasUp = numberUnsatisfied_;
882	choice[i].numIntInfeasDown = numberUnsatisfied_;
883	choice[i].fix = 0; // say not fixed
884	if (!dynamic_cast <const CbcSimpleInteger *> (model->object(choice[i].objectNumber)))
885	allNormal = false; // Something odd so lets skip clever fast branching
886	if ( !model->object(choice[i].objectNumber)->boundBranch())
887	numberStrong = 0; // switch off
888	if ( choice[i].possibleBranch->numberBranches() > 2)
889	numberStrong = 0; // switch off
890	// Do best choice in case switched off
891	if (choice[i].upMovement > worstInfeasibility) {
892	worstInfeasibility = choice[i].upMovement;
893	bestChoice = i;
894	}
895	}
896	//if (!model->parentModel())
897	//solver->writeMps("query");
898	// If we have hit max time don't do strong branching
899	bool hitMaxTime = (model->getCurrentSeconds() >
900	model->getDblParam(CbcModel::CbcMaximumSeconds));
901	// also give up if we are looping round too much
902	if (hitMaxTime \|\| numberPassesLeft <= 0)
903	numberStrong = 0;
904	/*
905	Is strong branching enabled? If so, set up and do it. Otherwise, we'll
906	fall through to simple branching.
907
908	Setup for strong branching involves saving the current basis (for restoration
909	afterwards) and setting up for hot starts.
910	*/
911	if (numberStrong && saveNumberStrong) {
912
913	bool solveAll = false; // set true to say look at all even if some fixed (experiment)
914	solveAll = true;
915	// worth trying if too many times
916	// Save basis
917	CoinWarmStart * ws = solver->getWarmStart();
918	// save limit
919	int saveLimit;
920	solver->getIntParam(OsiMaxNumIterationHotStart, saveLimit);
921	if (beforeSolution && saveLimit < 100)
922	solver->setIntParam(OsiMaxNumIterationHotStart, 100); // go to end
923	# ifdef COIN_HAS_CLP
924	/* If we are doing all strong branching in one go then we create new arrays
925	to store information. If clp NULL then doing old way.
926	Going down -
927	outputSolution[2*i] is final solution.
928	outputStuff[2*i] is status (0 - finished, 1 infeas, other unknown
929	outputStuff[2*i+numberStrong] is number iterations
930	On entry newUpper[i] is new upper bound, on exit obj change
931	Going up -
932	outputSolution[2*i+1] is final solution.
933	outputStuff[2*i+1] is status (0 - finished, 1 infeas, other unknown
934	outputStuff[2*i+1+numberStrong] is number iterations
935	On entry newLower[i] is new lower bound, on exit obj change
936	*/
937	ClpSimplex * clp = NULL;
938	double * newLower = NULL;
939	double * newUpper = NULL;
940	double ** outputSolution = NULL;
941	int * outputStuff = NULL;
942	// Go back to normal way if user wants it
943	if (osiclp && (osiclp->specialOptions()&16) != 0 && osiclp->specialOptions() > 0)
944	allNormal = false;
945	if (osiclp && !allNormal) {
946	// say do fast
947	int easy = 1;
948	osiclp->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, &easy) ;
949	}
950	if (osiclp && allNormal) {
951	clp = osiclp->getModelPtr();
952	// Clp - do a different way
953	newLower = new double[numberStrong];
954	newUpper = new double[numberStrong];
955	outputSolution = new double * [2*numberStrong];
956	outputStuff = new int [4*numberStrong];
957	int * which = new int[numberStrong];
958	int startFinishOptions;
959	int specialOptions = osiclp->specialOptions();
960	int clpOptions = clp->specialOptions();
961	int returnCode = 0;
962	#define CRUNCH
963	#ifdef CRUNCH
964	// Crunch down problem
965	int numberRows = clp->numberRows();
966	// Use dual region
967	double * rhs = clp->dualRowSolution();
968	int * whichRow = new int[3*numberRows];
969	int * whichColumn = new int[2*numberColumns];
970	int nBound;
971	ClpSimplex * small = static_cast<ClpSimplexOther *> (clp)->crunch(rhs, whichRow, whichColumn, nBound, true);
972	if (!small) {
973	anyAction = -2;
974	//printf("XXXX Inf by inspection\n");
975	delete [] whichColumn;
976	whichColumn = NULL;
977	delete [] whichRow;
978	whichRow = NULL;
979	break;
980	} else {
981	clp = small;
982	}
983	#else
984	int saveLogLevel = clp->logLevel();
985	int saveMaxIts = clp->maximumIterations();
986	#endif
987	clp->setLogLevel(0);
988	if ((specialOptions&1) == 0) {
989	startFinishOptions = 0;
990	clp->setSpecialOptions(clpOptions \| (64 \| 1024));
991	} else {
992	startFinishOptions = 1 + 2 + 4;
993	//startFinishOptions=1+4; // for moment re-factorize
994	if ((specialOptions&4) == 0)
995	clp->setSpecialOptions(clpOptions \| (64 \| 128 \| 512 \| 1024 \| 4096));
996	else
997	clp->setSpecialOptions(clpOptions \| (64 \| 128 \| 512 \| 1024 \| 2048 \| 4096));
998	}
999	// User may want to clean up before strong branching
1000	if ((clp->specialOptions()&32) != 0) {
1001	clp->primal(1);
1002	if (clp->numberIterations())
1003	model->messageHandler()->message(CBC_ITERATE_STRONG, *model->messagesPointer())
1004	<< clp->numberIterations()
1005	<< CoinMessageEol;
1006	}
1007	clp->setMaximumIterations(saveLimit);
1008	#ifdef CRUNCH
1009	int * backColumn = whichColumn + numberColumns;
1010	#endif
1011	for (i = 0; i < numberStrong; i++) {
1012	int iObject = choice[i].objectNumber;
1013	const OsiObject * object = model->object(iObject);
1014	const CbcSimpleInteger * simple = static_cast <const CbcSimpleInteger *> (object);
1015	int iSequence = simple->columnNumber();
1016	newLower[i] = ceil(saveSolution[iSequence]);
1017	newUpper[i] = floor(saveSolution[iSequence]);
1018	#ifdef CRUNCH
1019	iSequence = backColumn[iSequence];
1020	assert (iSequence >= 0);
1021	#endif
1022	which[i] = iSequence;
1023	outputSolution[2*i] = new double [numberColumns];
1024	outputSolution[2*i+1] = new double [numberColumns];
1025	}
1026	//clp->writeMps("bad");
1027	returnCode = clp->strongBranching(numberStrong, which,
1028	newLower, newUpper, outputSolution,
1029	outputStuff, outputStuff + 2 * numberStrong, !solveAll, false,
1030	startFinishOptions);
1031	#ifndef CRUNCH
1032	clp->setSpecialOptions(clpOptions); // restore
1033	clp->setMaximumIterations(saveMaxIts);
1034	clp->setLogLevel(saveLogLevel);
1035	#endif
1036	if (returnCode == -2) {
1037	// bad factorization!!!
1038	// Doing normal way
1039	// Mark hot start
1040	solver->markHotStart();
1041	clp = NULL;
1042	} else {
1043	#ifdef CRUNCH
1044	// extract solution
1045	//bool checkSol=true;
1046	for (i = 0; i < numberStrong; i++) {
1047	int iObject = choice[i].objectNumber;
1048	const OsiObject * object = model->object(iObject);
1049	const CbcSimpleInteger * simple = static_cast <const CbcSimpleInteger *> (object);
1050	int iSequence = simple->columnNumber();
1051	which[i] = iSequence;
1052	double * sol = outputSolution[2*i];
1053	double * sol2 = outputSolution[2*i+1];
1054	//bool x=true;
1055	//bool x2=true;
1056	for (int iColumn = numberColumns - 1; iColumn >= 0; iColumn--) {
1057	int jColumn = backColumn[iColumn];
1058	if (jColumn >= 0) {
1059	sol[iColumn] = sol[jColumn];
1060	sol2[iColumn] = sol2[jColumn];
1061	} else {
1062	sol[iColumn] = saveSolution[iColumn];
1063	sol2[iColumn] = saveSolution[iColumn];
1064	}
1065	}
1066	}
1067	#endif
1068	}
1069	#ifdef CRUNCH
1070	delete [] whichColumn;
1071	delete [] whichRow;
1072	delete small;
1073	#endif
1074	delete [] which;
1075	} else {
1076	// Doing normal way
1077	// Mark hot start
1078	solver->markHotStart();
1079	}
1080	# else /* COIN_HAS_CLP */
1081
1082	OsiSolverInterface *clp = NULL ;
1083	double **outputSolution = NULL ;
1084	int *outputStuff = NULL ;
1085	double * newLower = NULL ;
1086	double * newUpper = NULL ;
1087
1088	solver->markHotStart();
1089
1090	# endif /* COIN_HAS_CLP */
1091	/*
1092	Open a loop to do the strong branching LPs. For each candidate variable,
1093	solve an LP with the variable forced down, then up. If a direction turns
1094	out to be infeasible or monotonic (i.e., over the dual objective cutoff),
1095	force the objective change to be big (1.0e100). If we determine the problem
1096	is infeasible, or find a monotone variable, escape the loop.
1097
1098	TODO: The `restore bounds' part might be better encapsulated as an
1099	unbranch() method. Branching objects more exotic than simple integers
1100	or cliques might not restrict themselves to variable bounds.
1101
1102	TODO: Virtuous solvers invalidate the current solution (or give bogus
1103	results :-) when the bounds are changed out from under them. So we
1104	need to do all the work associated with finding a new solution before
1105	restoring the bounds.
1106	*/
1107	for (i = 0 ; i < numberStrong ; i++) {
1108	double objectiveChange ;
1109	double newObjectiveValue = 1.0e100;
1110	// status is 0 finished, 1 infeasible and other
1111	int iStatus;
1112	/*
1113	Try the down direction first. (Specify the initial branching alternative as
1114	down with a call to way(-1). Each subsequent call to branch() performs the
1115	specified branch and advances the branch object state to the next branch
1116	alternative.)
1117	*/
1118	if (!clp) {
1119	choice[i].possibleBranch->way(-1) ;
1120	choice[i].possibleBranch->branch() ;
1121	bool feasible = true;
1122	if (checkFeasibility) {
1123	// check branching did not make infeasible
1124	int iColumn;
1125	int numberColumns = solver->getNumCols();
1126	const double * columnLower = solver->getColLower();
1127	const double * columnUpper = solver->getColUpper();
1128	for (iColumn = 0; iColumn < numberColumns; iColumn++) {
1129	if (columnLower[iColumn] > columnUpper[iColumn] + 1.0e-5)
1130	feasible = false;
1131	}
1132	}
1133	if (feasible) {
1134	solver->solveFromHotStart() ;
1135	numberStrongDone++;
1136	numberStrongIterations += solver->getIterationCount();
1137	/*
1138	We now have an estimate of objective degradation that we can use for strong
1139	branching. If we're over the cutoff, the variable is monotone up.
1140	If we actually made it to optimality, check for a solution, and if we have
1141	a good one, call setBestSolution to process it. Note that this may reduce the
1142	cutoff, so we check again to see if we can declare this variable monotone.
1143	*/
1144	if (solver->isProvenOptimal())
1145	iStatus = 0; // optimal
1146	else if (solver->isIterationLimitReached()
1147	&& !solver->isDualObjectiveLimitReached())
1148	iStatus = 2; // unknown
1149	else
1150	iStatus = 1; // infeasible
1151	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
1152	choice[i].numItersDown = solver->getIterationCount();
1153	} else {
1154	iStatus = 1; // infeasible
1155	newObjectiveValue = 1.0e100;
1156	choice[i].numItersDown = 0;
1157	}
1158	} else {
1159	iStatus = outputStuff[2*i];
1160	choice[i].numItersDown = outputStuff[2numberStrong+2i];
1161	numberStrongDone++;
1162	numberStrongIterations += choice[i].numItersDown;
1163	newObjectiveValue = objectiveValue + newUpper[i];
1164	solver->setColSolution(outputSolution[2*i]);
1165	}
1166	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
1167	if (!iStatus) {
1168	choice[i].finishedDown = true ;
1169	if (newObjectiveValue >= model->getCutoff()) {
1170	objectiveChange = 1.0e100; // say infeasible
1171	numberStrongInfeasible++;
1172	} else {
1173	// See if integer solution
1174	if (model->feasibleSolution(choice[i].numIntInfeasDown,
1175	choice[i].numObjInfeasDown)
1176	&& model->problemFeasibility()->feasible(model, -1) >= 0) {
1177	model->setBestSolution(CBC_STRONGSOL,
1178	newObjectiveValue,
1179	solver->getColSolution()) ;
1180	// only needed for odd solvers
1181	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
1182	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0) ;
1183	model->setLastHeuristic(NULL);
1184	model->incrementUsed(solver->getColSolution());
1185	if (newObjectiveValue >= model->getCutoff()) { // new cutoff
1186	objectiveChange = 1.0e100 ;
1187	numberStrongInfeasible++;
1188	}
1189	}
1190	}
1191	} else if (iStatus == 1) {
1192	objectiveChange = 1.0e100 ;
1193	numberStrongInfeasible++;
1194	} else {
1195	// Can't say much as we did not finish
1196	choice[i].finishedDown = false ;
1197	numberUnfinished++;
1198	}
1199	choice[i].downMovement = objectiveChange ;
1200
1201	// restore bounds
1202	if (!clp) {
1203	for (int j = 0; j < numberColumns; j++) {
1204	if (saveLower[j] != lower[j])
1205	solver->setColLower(j, saveLower[j]);
1206	if (saveUpper[j] != upper[j])
1207	solver->setColUpper(j, saveUpper[j]);
1208	}
1209	}
1210	//printf("Down on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n",
1211	// choice[i].objectNumber,iStatus,newObjectiveValue,choice[i].numItersDown,
1212	// choice[i].downMovement,choice[i].finishedDown,choice[i].numIntInfeasDown,
1213	// choice[i].numObjInfeasDown);
1214
1215	// repeat the whole exercise, forcing the variable up
1216	if (!clp) {
1217	bool feasible = true;
1218	// If odd branching then maybe just one possibility
1219	if (choice[i].possibleBranch->numberBranchesLeft() > 0) {
1220	choice[i].possibleBranch->branch();
1221	if (checkFeasibility) {
1222	// check branching did not make infeasible
1223	int iColumn;
1224	int numberColumns = solver->getNumCols();
1225	const double * columnLower = solver->getColLower();
1226	const double * columnUpper = solver->getColUpper();
1227	for (iColumn = 0; iColumn < numberColumns; iColumn++) {
1228	if (columnLower[iColumn] > columnUpper[iColumn] + 1.0e-5)
1229	feasible = false;
1230	}
1231	}
1232	} else {
1233	// second branch infeasible
1234	feasible = false;
1235	}
1236	if (feasible) {
1237	solver->solveFromHotStart() ;
1238	numberStrongDone++;
1239	numberStrongIterations += solver->getIterationCount();
1240	/*
1241	We now have an estimate of objective degradation that we can use for strong
1242	branching. If we're over the cutoff, the variable is monotone up.
1243	If we actually made it to optimality, check for a solution, and if we have
1244	a good one, call setBestSolution to process it. Note that this may reduce the
1245	cutoff, so we check again to see if we can declare this variable monotone.
1246	*/
1247	if (solver->isProvenOptimal())
1248	iStatus = 0; // optimal
1249	else if (solver->isIterationLimitReached()
1250	&& !solver->isDualObjectiveLimitReached())
1251	iStatus = 2; // unknown
1252	else
1253	iStatus = 1; // infeasible
1254	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
1255	choice[i].numItersUp = solver->getIterationCount();
1256	} else {
1257	iStatus = 1; // infeasible
1258	newObjectiveValue = 1.0e100;
1259	choice[i].numItersDown = 0;
1260	}
1261	} else {
1262	iStatus = outputStuff[2*i+1];
1263	choice[i].numItersUp = outputStuff[2numberStrong+2i+1];
1264	numberStrongDone++;
1265	numberStrongIterations += choice[i].numItersUp;
1266	newObjectiveValue = objectiveValue + newLower[i];
1267	solver->setColSolution(outputSolution[2*i+1]);
1268	}
1269	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
1270	if (!iStatus) {
1271	choice[i].finishedUp = true ;
1272	if (newObjectiveValue >= model->getCutoff()) {
1273	objectiveChange = 1.0e100; // say infeasible
1274	numberStrongInfeasible++;
1275	} else {
1276	// See if integer solution
1277	if (model->feasibleSolution(choice[i].numIntInfeasUp,
1278	choice[i].numObjInfeasUp)
1279	&& model->problemFeasibility()->feasible(model, -1) >= 0) {
1280	model->setBestSolution(CBC_STRONGSOL,
1281	newObjectiveValue,
1282	solver->getColSolution()) ;
1283	// only needed for odd solvers
1284	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
1285	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0) ;
1286	model->setLastHeuristic(NULL);
1287	model->incrementUsed(solver->getColSolution());
1288	if (newObjectiveValue >= model->getCutoff()) { // new cutoff
1289	objectiveChange = 1.0e100 ;
1290	numberStrongInfeasible++;
1291	}
1292	}
1293	}
1294	} else if (iStatus == 1) {
1295	objectiveChange = 1.0e100 ;
1296	numberStrongInfeasible++;
1297	} else {
1298	// Can't say much as we did not finish
1299	choice[i].finishedUp = false ;
1300	numberUnfinished++;
1301	}
1302	choice[i].upMovement = objectiveChange ;
1303
1304	// restore bounds
1305	if (!clp) {
1306	for (int j = 0; j < numberColumns; j++) {
1307	if (saveLower[j] != lower[j])
1308	solver->setColLower(j, saveLower[j]);
1309	if (saveUpper[j] != upper[j])
1310	solver->setColUpper(j, saveUpper[j]);
1311	}
1312	}
1313
1314	//printf("Up on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n",
1315	// choice[i].objectNumber,iStatus,newObjectiveValue,choice[i].numItersUp,
1316	// choice[i].upMovement,choice[i].finishedUp,choice[i].numIntInfeasUp,
1317	// choice[i].numObjInfeasUp);
1318
1319	/*
1320	End of evaluation for this candidate variable. Possibilities are:
1321	* Both sides below cutoff; this variable is a candidate for branching.
1322	* Both sides infeasible or above the objective cutoff: no further action
1323	here. Break from the evaluation loop and assume the node will be purged
1324	by the caller.
1325	* One side below cutoff: Install the branch (i.e., fix the variable). Break
1326	from the evaluation loop and assume the node will be reoptimised by the
1327	caller.
1328	*/
1329	// reset
1330	choice[i].possibleBranch->resetNumberBranchesLeft();
1331	if (choice[i].upMovement < 1.0e100) {
1332	if (choice[i].downMovement < 1.0e100) {
1333	// feasible - no action
1334	} else {
1335	// up feasible, down infeasible
1336	anyAction = -1;
1337	//printf("Down infeasible for choice %d sequence %d\n",i,
1338	// model->object(choice[i].objectNumber)->columnNumber());
1339	if (!solveAll) {
1340	choice[i].possibleBranch->way(1);
1341	choice[i].possibleBranch->branch();
1342	break;
1343	} else {
1344	choice[i].fix = 1;
1345	}
1346	}
1347	} else {
1348	if (choice[i].downMovement < 1.0e100) {
1349	// down feasible, up infeasible
1350	anyAction = -1;
1351	//printf("Up infeasible for choice %d sequence %d\n",i,
1352	// model->object(choice[i].objectNumber)->columnNumber());
1353	if (!solveAll) {
1354	choice[i].possibleBranch->way(-1);
1355	choice[i].possibleBranch->branch();
1356	break;
1357	} else {
1358	choice[i].fix = -1;
1359	}
1360	} else {
1361	// neither side feasible
1362	anyAction = -2;
1363	//printf("Both infeasible for choice %d sequence %d\n",i,
1364	// model->object(choice[i].objectNumber)->columnNumber());
1365	break;
1366	}
1367	}
1368	bool hitMaxTime = (model->getCurrentSeconds() >
1369	model->getDblParam(CbcModel::CbcMaximumSeconds));
1370	if (hitMaxTime) {
1371	numberStrong = i + 1;
1372	break;
1373	}
1374	}
1375	if (!clp) {
1376	// Delete the snapshot
1377	solver->unmarkHotStart();
1378	} else {
1379	delete [] newLower;
1380	delete [] newUpper;
1381	delete [] outputStuff;
1382	int i;
1383	for (i = 0; i < 2*numberStrong; i++)
1384	delete [] outputSolution[i];
1385	delete [] outputSolution;
1386	}
1387	solver->setIntParam(OsiMaxNumIterationHotStart, saveLimit);
1388	// restore basis
1389	solver->setWarmStart(ws);
1390	// Unless infeasible we will carry on
1391	// But we could fix anyway
1392	if (anyAction == -1 && solveAll) {
1393	// apply and take off
1394	for (i = 0 ; i < numberStrong ; i++) {
1395	if (choice[i].fix) {
1396	choice[i].possibleBranch->way(choice[i].fix) ;
1397	choice[i].possibleBranch->branch() ;
1398	}
1399	}
1400	bool feasible = true;
1401	if (checkFeasibility) {
1402	// check branching did not make infeasible
1403	int iColumn;
1404	int numberColumns = solver->getNumCols();
1405	const double * columnLower = solver->getColLower();
1406	const double * columnUpper = solver->getColUpper();
1407	for (iColumn = 0; iColumn < numberColumns; iColumn++) {
1408	if (columnLower[iColumn] > columnUpper[iColumn] + 1.0e-5)
1409	feasible = false;
1410	}
1411	}
1412	if (feasible) {
1413	// can do quick optimality check
1414	int easy = 2;
1415	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, &easy) ;
1416	solver->resolve() ;
1417	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, NULL) ;
1418	feasible = solver->isProvenOptimal();
1419	}
1420	if (feasible) {
1421	memcpy(saveSolution, solver->getColSolution(), numberColumns*sizeof(double));
1422	model->reserveCurrentSolution(saveSolution);
1423	memcpy(saveLower, solver->getColLower(), numberColumns*sizeof(double));
1424	memcpy(saveUpper, solver->getColUpper(), numberColumns*sizeof(double));
1425	// Clean up all candidates whih are fixed
1426	int numberLeft = 0;
1427	for (i = 0 ; i < numberStrong ; i++) {
1428	CbcStrongInfo thisChoice = choice[i];
1429	choice[i].possibleBranch = NULL;
1430	const OsiObject * object = model->object(thisChoice.objectNumber);
1431	double infeasibility = object->checkInfeasibility(&usefulInfo);
1432	if (!infeasibility) {
1433	// take out
1434	delete thisChoice.possibleBranch;
1435	} else {
1436	choice[numberLeft++] = thisChoice;
1437	}
1438	}
1439	numberStrong = numberLeft;
1440	for (; i < maximumStrong; i++) {
1441	delete choice[i].possibleBranch;
1442	choice[i].possibleBranch = NULL;
1443	}
1444	// If all fixed then round again
1445	if (!numberLeft) {
1446	finished = false;
1447	numberStrong = 0;
1448	saveNumberStrong = 0;
1449	maximumStrong = 1;
1450	} else {
1451	anyAction = 0;
1452	}
1453	// If these two uncommented then different action
1454	anyAction = -1;
1455	finished = true;
1456	//printf("some fixed but continuing %d left\n",numberLeft);
1457	} else {
1458	anyAction = -2; // say infeasible
1459	}
1460	}
1461	delete ws;
1462	//int numberNodes = model->getNodeCount();
1463	// update number of strong iterations etc
1464	model->incrementStrongInfo(numberStrongDone, numberStrongIterations,
1465	anyAction == -2 ? 0 : numberStrongInfeasible, anyAction == -2);
1466
1467	/*
1468	anyAction >= 0 indicates that strong branching didn't produce any monotone
1469	variables. Sift through the candidates for the best one.
1470
1471	QUERY: Setting numberNodes looks to be a distributed noop. numberNodes is
1472	local to this code block. Perhaps should be numberNodes_ from model?
1473	Unclear what this calculation is doing.
1474	*/
1475	if (anyAction >= 0) {
1476
1477	// get average cost per iteration and assume stopped ones
1478	// would stop after 50% more iterations at average cost??? !!! ???
1479	double averageCostPerIteration = 0.0;
1480	double totalNumberIterations = 1.0;
1481	int smallestNumberInfeasibilities = COIN_INT_MAX;
1482	for (i = 0; i < numberStrong; i++) {
1483	totalNumberIterations += choice[i].numItersDown +
1484	choice[i].numItersUp ;
1485	averageCostPerIteration += choice[i].downMovement +
1486	choice[i].upMovement;
1487	smallestNumberInfeasibilities =
1488	CoinMin(CoinMin(choice[i].numIntInfeasDown ,
1489	choice[i].numIntInfeasUp ),
1490	smallestNumberInfeasibilities);
1491	}
1492	//if (smallestNumberInfeasibilities>=numberIntegerInfeasibilities)
1493	//numberNodes=1000000; // switch off search for better solution
1494	averageCostPerIteration /= totalNumberIterations;
1495	// all feasible - choose best bet
1496
1497	// New method does all at once so it can be more sophisticated
1498	// in deciding how to balance actions.
1499	// But it does need arrays
1500	double * changeUp = new double [numberStrong];
1501	int * numberInfeasibilitiesUp = new int [numberStrong];
1502	double * changeDown = new double [numberStrong];
1503	int * numberInfeasibilitiesDown = new int [numberStrong];
1504	CbcBranchingObject ** objects = new CbcBranchingObject * [ numberStrong];
1505	for (i = 0 ; i < numberStrong ; i++) {
1506	int iColumn = choice[i].possibleBranch->variable() ;
1507	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
1508	<< i << iColumn
1509	<< choice[i].downMovement << choice[i].numIntInfeasDown
1510	<< choice[i].upMovement << choice[i].numIntInfeasUp
1511	<< choice[i].possibleBranch->value()
1512	<< CoinMessageEol;
1513	changeUp[i] = choice[i].upMovement;
1514	numberInfeasibilitiesUp[i] = choice[i].numIntInfeasUp;
1515	changeDown[i] = choice[i].downMovement;
1516	numberInfeasibilitiesDown[i] = choice[i].numIntInfeasDown;
1517	objects[i] = choice[i].possibleBranch;
1518	}
1519	int whichObject = decision->bestBranch(objects, numberStrong, numberUnsatisfied_,
1520	changeUp, numberInfeasibilitiesUp,
1521	changeDown, numberInfeasibilitiesDown,
1522	objectiveValue_);
1523	// move branching object and make sure it will not be deleted
1524	if (whichObject >= 0) {
1525	branch_ = objects[whichObject];
1526	if (model->messageHandler()->logLevel() > 3)
1527	printf("Choosing column %d\n", choice[whichObject].possibleBranch->variable()) ;
1528	choice[whichObject].possibleBranch = NULL;
1529	}
1530	delete [] changeUp;
1531	delete [] numberInfeasibilitiesUp;
1532	delete [] changeDown;
1533	delete [] numberInfeasibilitiesDown;
1534	delete [] objects;
1535	}
1536	# ifdef COIN_HAS_CLP
1537	if (osiclp && !allNormal) {
1538	// back to normal
1539	osiclp->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, NULL) ;
1540	}
1541	# endif
1542	}
1543	/*
1544	Simple branching. Probably just one, but we may have got here
1545	because of an odd branch e.g. a cut
1546	*/
1547	else {
1548	// not strong
1549	// C) create branching object
1550	branch_ = choice[bestChoice].possibleBranch;
1551	choice[bestChoice].possibleBranch = NULL;
1552	}
1553	}
1554	// Set guessed solution value
1555	guessedObjectiveValue_ = objectiveValue_ + estimatedDegradation;
1556	//printf ("Node %d depth %d unsatisfied %d sum %g obj %g guess %g\n",
1557	// model->getNodeCount(),depth_,numberUnsatisfied_,
1558	// sumInfeasibilities_,objectiveValue_,guessedObjectiveValue_);
1559	/*
1560	Cleanup, then we're outta here.
1561	*/
1562	if (!model->branchingMethod() \|\| dynamicBranchingObject)
1563	delete decision;
1564
1565	for (i = 0; i < maximumStrong; i++)
1566	delete choice[i].possibleBranch;
1567	delete [] choice;
1568	delete [] saveLower;
1569	delete [] saveUpper;
1570
1571	// restore solution
1572	solver->setColSolution(saveSolution);
1573	delete [] saveSolution;
1574	# ifdef COIN_HAS_CLP
1575	if (osiclp)
1576	osiclp->setSpecialOptions(saveClpOptions);
1577	# endif
1578	return anyAction;
1579	}
1580
1581	/*
1582	Version for dynamic pseudo costs.
1583
1584	**** For now just return if anything odd
1585	later allow even if odd
1586
1587	The routine scans through the object list of the model looking for objects
1588	that indicate infeasibility. It tests each object using strong branching
1589	and selects the one with the least objective degradation. A corresponding
1590	branching object is left attached to lastNode.
1591	This version gives preference in evaluation to variables which
1592	have not been evaluated many times. It also uses numberStrong
1593	to say give up if last few tries have not changed incumbent.
1594	See Achterberg, Koch and Martin.
1595
1596	If strong branching is disabled, a candidate object is chosen essentially
1597	at random (whatever object ends up in pos'n 0 of the candidate array).
1598
1599	If a branching candidate is found to be monotone, bounds are set to fix the
1600	variable and the routine immediately returns (the caller is expected to
1601	reoptimize).
1602
1603	If a branching candidate is found to result in infeasibility in both
1604	directions, the routine immediately returns an indication of infeasibility.
1605
1606	Returns: 0 both branch directions are feasible
1607	-1 branching variable is monotone
1608	-2 infeasible
1609	-3 Use another method
1610
1611	For now just fix on objective from strong branching.
1612	*/
1613
1614	int CbcNode::chooseDynamicBranch (CbcModel model, CbcNode lastNode,
1615	OsiSolverBranch * & /branches/,
1616	int numberPassesLeft)
1617
1618	{
1619	if (lastNode)
1620	depth_ = lastNode->depth_ + 1;
1621	else
1622	depth_ = 0;
1623	// Go to other choose if hot start
1624	if (model->hotstartSolution() &&
1625	(((model->moreSpecialOptions()&1024) == 0) \|\| false))
1626	return -3;
1627	delete branch_;
1628	branch_ = NULL;
1629	OsiSolverInterface * solver = model->solver();
1630	//#define CHECK_DEBUGGER_PATH
1631	#ifdef CHECK_DEBUGGER_PATH
1632	bool onOptimalPath=false;
1633	if ((model->specialOptions()&1) != 0) {
1634	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
1635	if (debugger) {
1636	onOptimalPath = true;
1637	}
1638	}
1639	#endif
1640	// get information on solver type
1641	const OsiAuxInfo * auxInfo = solver->getAuxiliaryInfo();
1642	const OsiBabSolver * auxiliaryInfo = dynamic_cast<const OsiBabSolver *> (auxInfo);
1643	if (!auxiliaryInfo) {
1644	// use one from CbcModel
1645	auxiliaryInfo = model->solverCharacteristics();
1646	}
1647	int numberObjects = model->numberObjects();
1648	// If very odd set of objects then use older chooseBranch
1649	bool useOldWay = false;
1650	// point to useful information
1651	OsiBranchingInformation usefulInfo = model->usefulInformation();
1652	if (numberObjects > model->numberIntegers()) {
1653	for (int i = model->numberIntegers(); i < numberObjects; i++) {
1654	OsiObject * object = model->modifiableObject(i);
1655	CbcObject * obj = dynamic_cast <CbcObject *>(object) ;
1656	if (!obj \|\| !obj->optionalObject()) {
1657	double infeasibility = object->checkInfeasibility(&usefulInfo);
1658	if (infeasibility) {
1659	useOldWay = true;
1660	break;
1661	}
1662	} else {
1663	obj->initializeForBranching(model);
1664	}
1665	}
1666	}
1667	if ((model->specialOptions()&128) != 0)
1668	useOldWay = false; // allow
1669	// For now return if not simple
1670	if (useOldWay)
1671	return -3;
1672	// Modify useful info
1673	usefulInfo.depth_ = depth_;
1674	if ((model->specialOptions()&128) != 0) {
1675	// SOS - shadow prices
1676	int numberRows = solver->getNumRows();
1677	const double * pi = usefulInfo.pi_;
1678	double sumPi = 0.0;
1679	for (int i = 0; i < numberRows; i++)
1680	sumPi += fabs(pi[i]);
1681	sumPi /= static_cast<double> (numberRows);
1682	// and scale back
1683	sumPi *= 0.01;
1684	usefulInfo.defaultDual_ = sumPi; // switch on
1685	int numberColumns = solver->getNumCols();
1686	int size = CoinMax(numberColumns, 2 * numberRows);
1687	usefulInfo.usefulRegion_ = new double [size];
1688	CoinZeroN(usefulInfo.usefulRegion_, size);
1689	usefulInfo.indexRegion_ = new int [size];
1690	// pi may change
1691	usefulInfo.pi_ = CoinCopyOfArray(usefulInfo.pi_, numberRows);
1692	}
1693	assert (auxiliaryInfo);
1694	double cutoff = model->getCutoff();
1695	const double * lower = solver->getColLower();
1696	const double * upper = solver->getColUpper();
1697	// See if user thinks infeasible
1698	int anyAction = model->problemFeasibility()->feasible(model, 0);
1699	if (anyAction) {
1700	// will return -2 if infeasible , 0 if treat as integer
1701	return anyAction - 1;
1702	}
1703	int i;
1704	int saveStateOfSearch = model->stateOfSearch() % 10;
1705	int numberStrong = model->numberStrong();
1706	/* Ranging is switched off.
1707	The idea is that you can find out the effect of one iteration
1708	on each unsatisfied variable cheaply. Then use this
1709	if you have not got much else to go on.
1710	*/
1711	//#define RANGING
1712	#ifdef RANGING
1713	// must have clp
1714	#ifndef COIN_HAS_CLP
1715	# warning("Ranging switched off as not Clp");
1716	#undef RANGING
1717	#endif
1718	// Pass number
1719	int kPass = 0;
1720	int numberRows = solver->getNumRows();
1721	#endif
1722	int numberColumns = model->getNumCols();
1723	double * saveUpper = new double[numberColumns];
1724	double * saveLower = new double[numberColumns];
1725	for (i = 0; i < numberColumns; i++) {
1726	saveLower[i] = lower[i];
1727	saveUpper[i] = upper[i];
1728	}
1729
1730	// Save solution in case heuristics need good solution later
1731
1732	double * saveSolution = new double[numberColumns];
1733	memcpy(saveSolution, solver->getColSolution(), numberColumns*sizeof(double));
1734	model->reserveCurrentSolution(saveSolution);
1735	const double * hotstartSolution = model->hotstartSolution();
1736	const int * hotstartPriorities = model->hotstartPriorities();
1737	double integerTolerance =
1738	model->getDblParam(CbcModel::CbcIntegerTolerance);
1739	if (hotstartSolution) {
1740	if ((model->moreSpecialOptions()&1024) != 0) {
1741	int nBad = 0;
1742	int nUnsat = 0;
1743	int nDiff = 0;
1744	for (int i = 0; i < numberObjects; i++) {
1745	OsiObject * object = model->modifiableObject(i);
1746	const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object);
1747	if (thisOne) {
1748	int iColumn = thisOne->columnNumber();
1749	double targetValue = hotstartSolution[iColumn];
1750	double value = saveSolution[iColumn];
1751	if (fabs(value - floor(value + 0.5)) > 1.0e-6) {
1752	nUnsat++;
1753	#ifdef CLP_INVESTIGATE
1754	printf("H %d is %g target %g\n", iColumn, value, targetValue);
1755	#endif
1756	} else if (fabs(targetValue - value) > 1.0e-6) {
1757	nDiff++;
1758	}
1759	if (targetValue < saveLower[iColumn] \|\|
1760	targetValue > saveUpper[iColumn]) {
1761	#ifdef CLP_INVESTIGATE
1762	printf("%d has target %g and current bounds %g and %g\n",
1763	iColumn, targetValue, saveLower[iColumn], saveUpper[iColumn]);
1764	#endif
1765	nBad++;
1766	}
1767	}
1768	}
1769	#ifdef CLP_INVESTIGATE
1770	printf("Hot %d unsatisfied, %d outside limits, %d different\n",
1771	nUnsat, nBad, nDiff);
1772	#endif
1773	if (nBad) {
1774	// switch off as not possible
1775	hotstartSolution = NULL;
1776	model->setHotstartSolution(NULL, NULL);
1777	usefulInfo.hotstartSolution_ = NULL;
1778	}
1779	}
1780	}
1781	/*
1782	Get a branching decision object. Use the default dynamic decision criteria unless
1783	the user has loaded a decision method into the model.
1784	*/
1785	CbcBranchDecision *decision = model->branchingMethod();
1786	if (!decision)
1787	decision = new CbcBranchDynamicDecision();
1788	int xMark = 0;
1789	// Get arrays to sort
1790	double * sort = new double[numberObjects];
1791	int * whichObject = new int[numberObjects];
1792	#ifdef RANGING
1793	int xPen = 0;
1794	int * objectMark = new int[2*numberObjects+1];
1795	#endif
1796	// Arrays with movements
1797	double * upEstimate = new double[numberObjects];
1798	double * downEstimate = new double[numberObjects];
1799	double estimatedDegradation = 0.0;
1800	int numberNodes = model->getNodeCount();
1801	int saveLogLevel = model->logLevel();
1802	#ifdef JJF_ZERO
1803	if ((numberNodes % 500) == 0) {
1804	model->setLogLevel(6);
1805	// Get average up and down costs
1806	double averageUp = 0.0;
1807	double averageDown = 0.0;
1808	int numberUp = 0;
1809	int numberDown = 0;
1810	int i;
1811	for ( i = 0; i < numberObjects; i++) {
1812	OsiObject * object = model->modifiableObject(i);
1813	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
1814	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
1815	assert(dynamicObject);
1816	int numberUp2 = 0;
1817	int numberDown2 = 0;
1818	double up = 0.0;
1819	double down = 0.0;
1820	if (dynamicObject->numberTimesUp()) {
1821	numberUp++;
1822	averageUp += dynamicObject->upDynamicPseudoCost();
1823	numberUp2 += dynamicObject->numberTimesUp();
1824	up = dynamicObject->upDynamicPseudoCost();
1825	}
1826	if (dynamicObject->numberTimesDown()) {
1827	numberDown++;
1828	averageDown += dynamicObject->downDynamicPseudoCost();
1829	numberDown2 += dynamicObject->numberTimesDown();
1830	down = dynamicObject->downDynamicPseudoCost();
1831	}
1832	if (numberUp2 \|\| numberDown2)
1833	printf("col %d - up %d times cost %g, - down %d times cost %g\n",
1834	dynamicObject->columnNumber(), numberUp2, up, numberDown2, down);
1835	}
1836	if (numberUp)
1837	averageUp /= static_cast<double> (numberUp);
1838	else
1839	averageUp = 1.0;
1840	if (numberDown)
1841	averageDown /= static_cast<double> (numberDown);
1842	else
1843	averageDown = 1.0;
1844	printf("total - up %d vars average %g, - down %d vars average %g\n",
1845	numberUp, averageUp, numberDown, averageDown);
1846	}
1847	#endif
1848	int numberBeforeTrust = model->numberBeforeTrust();
1849	// May go round twice if strong branching fixes all local candidates
1850	bool finished = false;
1851	int numberToFix = 0;
1852	# ifdef COIN_HAS_CLP
1853	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
1854	int saveClpOptions = 0;
1855	if (osiclp) {
1856	// for faster hot start
1857	saveClpOptions = osiclp->specialOptions();
1858	osiclp->setSpecialOptions(saveClpOptions \| 8192);
1859	}
1860	# else
1861	OsiSolverInterface *osiclp = NULL ;
1862	# endif
1863	//const CglTreeProbingInfo * probingInfo = NULL; //model->probingInfo();
1864	// Old code left in with DEPRECATED_STRATEGY
1865	assert (model->searchStrategy() == -1 \|\|
1866	model->searchStrategy() == 1 \|\|
1867	model->searchStrategy() == 2);
1868	#ifdef DEPRECATED_STRATEGY
1869	int saveSearchStrategy2 = model->searchStrategy();
1870	#endif
1871	// Get average up and down costs
1872	{
1873	double averageUp = 0.0;
1874	double averageDown = 0.0;
1875	int numberUp = 0;
1876	int numberDown = 0;
1877	int i;
1878	for ( i = 0; i < numberObjects; i++) {
1879	OsiObject * object = model->modifiableObject(i);
1880	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
1881	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
1882	if (dynamicObject) {
1883	if (dynamicObject->numberTimesUp()) {
1884	numberUp++;
1885	averageUp += dynamicObject->upDynamicPseudoCost();
1886	}
1887	if (dynamicObject->numberTimesDown()) {
1888	numberDown++;
1889	averageDown += dynamicObject->downDynamicPseudoCost();
1890	}
1891	}
1892	}
1893	if (numberUp)
1894	averageUp /= static_cast<double> (numberUp);
1895	else
1896	averageUp = 1.0;
1897	if (numberDown)
1898	averageDown /= static_cast<double> (numberDown);
1899	else
1900	averageDown = 1.0;
1901	for ( i = 0; i < numberObjects; i++) {
1902	OsiObject * object = model->modifiableObject(i);
1903	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
1904	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
1905	if (dynamicObject) {
1906	if (!dynamicObject->numberTimesUp())
1907	dynamicObject->setUpDynamicPseudoCost(averageUp);
1908	if (!dynamicObject->numberTimesDown())
1909	dynamicObject->setDownDynamicPseudoCost(averageDown);
1910	}
1911	}
1912	}
1913	/*
1914	1 strong
1915	2 no strong
1916	3 strong just before solution
1917	4 no strong just before solution
1918	5 strong first time or before solution
1919	6 strong first time
1920	*/
1921	int useShadow = model->moreSpecialOptions() & 7;
1922	if (useShadow > 2) {
1923	if (model->getSolutionCount()) {
1924	if (numberNodes \|\| useShadow < 5) {
1925	useShadow = 0;
1926	// zap pseudo shadow prices
1927	model->pseudoShadow(-1);
1928	// and switch off
1929	model->setMoreSpecialOptions(model->moreSpecialOptions()&(~1023));
1930	} else {
1931	useShadow = 1;
1932	}
1933	} else if (useShadow < 5) {
1934	useShadow -= 2;
1935	} else {
1936	useShadow = 1;
1937	}
1938	}
1939	if (useShadow) {
1940	// pseudo shadow prices
1941	model->pseudoShadow((model->moreSpecialOptions() >> 3)&63);
1942	}
1943	#ifdef DEPRECATED_STRATEGY
1944	{ // in for tabbing
1945	} else if (saveSearchStrategy2 < 1999) {
1946	// pseudo shadow prices
1947	model->pseudoShadow(NULL, NULL);
1948	} else if (saveSearchStrategy2 < 2999) {
1949	// leave old ones
1950	} else if (saveSearchStrategy2 < 3999) {
1951	// pseudo shadow prices at root
1952	if (!numberNodes)
1953	model->pseudoShadow(NULL, NULL);
1954	} else {
1955	abort();
1956	}
1957	if (saveSearchStrategy2 >= 0)
1958	saveSearchStrategy2 = saveSearchStrategy2 % 1000;
1959	if (saveSearchStrategy2 == 999)
1960	saveSearchStrategy2 = -1;
1961	int saveSearchStrategy = saveSearchStrategy2 < 99 ? saveSearchStrategy2 : saveSearchStrategy2 - 100;
1962	#endif //DEPRECATED_STRATEGY
1963	int numberNotTrusted = 0;
1964	int numberStrongDone = 0;
1965	int numberUnfinished = 0;
1966	int numberStrongInfeasible = 0;
1967	int numberStrongIterations = 0;
1968	int strongType=0;
1969	#define DO_ALL_AT_ROOT
1970	#ifdef DO_ALL_AT_ROOT
1971	int saveSatisfiedVariables=0;
1972	int saveNumberToDo=0;
1973	#endif
1974	// so we can save lots of stuff
1975	CbcStrongInfo choice;
1976	CbcDynamicPseudoCostBranchingObject * choiceObject = NULL;
1977	if (model->allDynamic()) {
1978	CbcSimpleIntegerDynamicPseudoCost * object = NULL;
1979	choiceObject = new CbcDynamicPseudoCostBranchingObject(model, 0, -1, 0.5, object);
1980	}
1981	choice.possibleBranch = choiceObject;
1982	numberPassesLeft = CoinMax(numberPassesLeft, 2);
1983	/* How dogged to be in strong branching
1984	0 - default
1985	1 - go to end on first time
1986	2 - always go to end
1987	*/
1988	int goToEndInStrongBranching = (model->moreSpecialOptions2()&(3*8192))>>13;
1989	#ifdef COIN_HAS_NTY
1990	// 1 after, 2 strong, 3 until depth 5
1991	int orbitOption = (model->moreSpecialOptions2()&(128\|256))>>7;
1992	#endif
1993	//#define DEBUG_SOLUTION
1994	#ifdef DEBUG_SOLUTION
1995	bool onOptimalPath=false;
1996	if ((model->specialOptions()&1) != 0) {
1997	const OsiRowCutDebugger *debugger = model->continuousSolver()->getRowCutDebugger() ;
1998	if (debugger) {
1999	const OsiRowCutDebugger *debugger2 = model->solver()->getRowCutDebugger() ;
2000	printf("On optimal in CbcNode %s\n",debugger2 ? "" : "but bad cuts");
2001	onOptimalPath=true;
2002	}
2003	}
2004	#endif
2005	while (!finished) {
2006	numberPassesLeft--;
2007	finished = true;
2008	decision->initialize(model);
2009	// Some objects may compute an estimate of best solution from here
2010	estimatedDegradation = 0.0;
2011	numberToFix = 0;
2012	int numberToDo = 0;
2013	int iBestNot = -1;
2014	int iBestGot = -1;
2015	double best = 0.0;
2016	numberNotTrusted = 0;
2017	numberStrongDone = 0;
2018	numberUnfinished = 0;
2019	numberStrongInfeasible = 0;
2020	numberStrongIterations = 0;
2021	#ifdef RANGING
2022	int * which = objectMark + numberObjects + 1;
2023	int neededPenalties;
2024	int optionalPenalties;
2025	#endif
2026	// We may go round this loop three times (only if we think we have solution)
2027	for (int iPass = 0; iPass < 3; iPass++) {
2028
2029	// Some objects may compute an estimate of best solution from here
2030	estimatedDegradation = 0.0;
2031	numberUnsatisfied_ = 0;
2032	// initialize sum of "infeasibilities"
2033	sumInfeasibilities_ = 0.0;
2034	int bestPriority = COIN_INT_MAX;
2035	#ifdef JJF_ZERO
2036	int number01 = 0;
2037	const cliqueEntry * entry = NULL;
2038	const int * toZero = NULL;
2039	const int * toOne = NULL;
2040	const int * backward = NULL;
2041	int numberUnsatisProbed = 0;
2042	int numberUnsatisNotProbed = 0; // 0-1
2043	if (probingInfo) {
2044	number01 = probingInfo->numberIntegers();
2045	entry = probingInfo->fixEntries();
2046	toZero = probingInfo->toZero();
2047	toOne = probingInfo->toOne();
2048	backward = probingInfo->backward();
2049	if (!toZero[number01] \|\| number01 < numberObjects \|\| true) {
2050	// no info
2051	probingInfo = NULL;
2052	}
2053	}
2054	#endif
2055	/*
2056	Scan for branching objects that indicate infeasibility. Choose candidates
2057	using priority as the first criteria, then integer infeasibility.
2058
2059	The algorithm is to fill the array with a set of good candidates (by
2060	infeasibility) with priority bestPriority. Finding a candidate with
2061	priority better (less) than bestPriority flushes the choice array. (This
2062	serves as initialization when the first candidate is found.)
2063
2064	*/
2065	numberToDo = 0;
2066	#ifdef RANGING
2067	neededPenalties = 0;
2068	optionalPenalties = numberObjects;
2069	#endif
2070	iBestNot = -1;
2071	double bestNot = 0.0;
2072	iBestGot = -1;
2073	best = 0.0;
2074	/* Problem type as set by user or found by analysis. This will be extended
2075	0 - not known
2076	1 - Set partitioning <=
2077	2 - Set partitioning ==
2078	3 - Set covering
2079	4 - all +- 1 or all +1 and odd
2080	*/
2081	int problemType = model->problemType();
2082	bool canDoOneHot = false;
2083	for (i = 0; i < numberObjects; i++) {
2084	OsiObject * object = model->modifiableObject(i);
2085	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
2086	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
2087	double infeasibility = object->checkInfeasibility(&usefulInfo);
2088	int priorityLevel = object->priority();
2089	if (hotstartSolution) {
2090	// we are doing hot start
2091	const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object);
2092	if (thisOne) {
2093	int iColumn = thisOne->columnNumber();
2094	bool canDoThisHot = true;
2095	double targetValue = hotstartSolution[iColumn];
2096	if (saveUpper[iColumn] > saveLower[iColumn]) {
2097	double value = saveSolution[iColumn];
2098	if (hotstartPriorities)
2099	priorityLevel = hotstartPriorities[iColumn];
2100	//double originalLower = thisOne->originalLower();
2101	//double originalUpper = thisOne->originalUpper();
2102	// switch off if not possible
2103	if (targetValue >= saveLower[iColumn] && targetValue <= saveUpper[iColumn]) {
2104	/* priority outranks rest always if negative
2105	otherwise can be downgraded if at correct level.
2106	Infeasibility may be increased to choose 1.0 values first.
2107	choose one near wanted value
2108	*/
2109	if (fabs(value - targetValue) > integerTolerance) {
2110	//if (infeasibility>0.01)
2111	//infeasibility = fabs(1.0e6-fabs(value-targetValue));
2112	//else
2113	infeasibility = fabs(value - targetValue);
2114	priorityLevel = CoinAbs(priorityLevel);
2115	} else if (priorityLevel < 0) {
2116	priorityLevel = CoinAbs(priorityLevel);
2117	if (targetValue == saveLower[iColumn] \|\|
2118	targetValue == saveUpper[iColumn]) {
2119	infeasibility = integerTolerance + 1.0e-12;
2120	} else {
2121	// can't
2122	priorityLevel += 10000000;
2123	canDoThisHot = false;
2124	}
2125	} else {
2126	priorityLevel += 10000000;
2127	canDoThisHot = false;
2128	}
2129	} else {
2130	// switch off if not possible
2131	canDoThisHot = false;
2132	}
2133	if (canDoThisHot)
2134	canDoOneHot = true;
2135	} else if (targetValue < saveLower[iColumn] \|\| targetValue > saveUpper[iColumn]) {
2136	}
2137	} else {
2138	priorityLevel += 10000000;
2139	}
2140	}
2141	#define ZERO_ONE 0
2142	#define ZERO_FAKE 1.0e20;
2143	#if ZERO_ONE==1
2144	// branch on 0-1 first (temp)
2145	if (fabs(saveSolution[dynamicObject->columnNumber()]) < 1.0)
2146	priorityLevel--;
2147	#endif
2148	#if ZERO_ONE==2
2149	if (fabs(saveSolution[dynamicObject->columnNumber()]) < 1.0)
2150	infeasibility *= ZERO_FAKE;
2151	#endif
2152	if (infeasibility) {
2153	int iColumn = numberColumns + i;
2154	bool gotDown = false;
2155	int numberThisDown = 0;
2156	bool gotUp = false;
2157	int numberThisUp = 0;
2158	double downGuess = object->downEstimate();
2159	double upGuess = object->upEstimate();
2160	if (dynamicObject) {
2161	// Use this object's numberBeforeTrust
2162	int numberBeforeTrustThis = dynamicObject->numberBeforeTrust();
2163	iColumn = dynamicObject->columnNumber();
2164	gotDown = false;
2165	numberThisDown = dynamicObject->numberTimesDown();
2166	if (numberThisDown >= numberBeforeTrustThis)
2167	gotDown = true;
2168	gotUp = false;
2169	numberThisUp = dynamicObject->numberTimesUp();
2170	if (numberThisUp >= numberBeforeTrustThis)
2171	gotUp = true;
2172	if (!depth_ && false) {
2173	// try closest to 0.5
2174	double part = saveSolution[iColumn] - floor(saveSolution[iColumn]);
2175	infeasibility = fabs(0.5 - part);
2176	}
2177	if (problemType > 0 && problemType < 4 && false) {
2178	// try closest to 0.5
2179	double part = saveSolution[iColumn] - floor(saveSolution[iColumn]);
2180	infeasibility = 0.5 - fabs(0.5 - part);
2181	}
2182	#ifdef JJF_ZERO
2183	if (probingInfo) {
2184	int iSeq = backward[iColumn];
2185	assert (iSeq >= 0);
2186	infeasibility = 1.0 + (toZero[iSeq+1] - toZero[iSeq]) +
2187	5.0 * CoinMin(toOne[iSeq] - toZero[iSeq], toZero[iSeq+1] - toOne[iSeq]);
2188	if (toZero[iSeq+1] > toZero[iSeq]) {
2189	numberUnsatisProbed++;
2190	} else {
2191	numberUnsatisNotProbed++;
2192	}
2193	}
2194	#endif
2195	} else {
2196	// see if SOS
2197	CbcSOS * sosObject =
2198	dynamic_cast <CbcSOS *>(object) ;
2199	if (sosObject) {
2200	gotDown = false;
2201	numberThisDown = sosObject->numberTimesDown();
2202	if (numberThisDown >= numberBeforeTrust)
2203	gotDown = true;
2204	gotUp = false;
2205	numberThisUp = sosObject->numberTimesUp();
2206	if (numberThisUp >= numberBeforeTrust)
2207	gotUp = true;
2208	} else {
2209	gotDown = true;
2210	numberThisDown = 999999;
2211	downGuess = 1.0e20;
2212	gotUp = true;
2213	numberThisUp = 999999;
2214	upGuess = 1.0e20;
2215	numberPassesLeft = 0;
2216	}
2217	}
2218	// Increase estimated degradation to solution
2219	estimatedDegradation += CoinMin(downGuess, upGuess);
2220	downEstimate[i] = downGuess;
2221	upEstimate[i] = upGuess;
2222	numberUnsatisfied_++;
2223	sumInfeasibilities_ += infeasibility;
2224	// Better priority? Flush choices.
2225	if (priorityLevel < bestPriority) {
2226	numberToDo = 0;
2227	bestPriority = priorityLevel;
2228	iBestGot = -1;
2229	best = 0.0;
2230	numberNotTrusted = 0;
2231	#ifdef RANGING
2232	neededPenalties = 0;
2233	optionalPenalties = numberObjects;
2234	#endif
2235	} else if (priorityLevel > bestPriority) {
2236	continue;
2237	}
2238	if (!gotUp \|\| !gotDown)
2239	numberNotTrusted++;
2240	// Check for suitability based on infeasibility.
2241	if ((gotDown && gotUp) && numberStrong > 0) {
2242	sort[numberToDo] = -infeasibility;
2243	if (infeasibility > best) {
2244	best = infeasibility;
2245	iBestGot = numberToDo;
2246	}
2247	#ifdef RANGING
2248	if (dynamicObject) {
2249	objectMark[--optionalPenalties] = numberToDo;
2250	which[optionalPenalties] = iColumn;
2251	}
2252	#endif
2253	} else {
2254	#ifdef RANGING
2255	if (dynamicObject) {
2256	objectMark[neededPenalties] = numberToDo;
2257	which[neededPenalties++] = iColumn;
2258	}
2259	#endif
2260	sort[numberToDo] = -10.0 * infeasibility;
2261	if (!(numberThisUp + numberThisDown))
2262	sort[numberToDo] *= 100.0; // make even more likely
2263	if (iColumn < numberColumns) {
2264	double part = saveSolution[iColumn] - floor(saveSolution[iColumn]);
2265	if (1.0 - fabs(part - 0.5) > bestNot) {
2266	iBestNot = numberToDo;
2267	bestNot = 1.0 - fabs(part - 0.5);
2268	}
2269	} else {
2270	// SOS
2271	if (-sort[numberToDo] > bestNot) {
2272	iBestNot = numberToDo;
2273	bestNot = -sort[numberToDo];
2274	}
2275	}
2276	}
2277	if (model->messageHandler()->logLevel() > 3) {
2278	printf("%d (%d) down %d %g up %d %g - infeas %g - sort %g solution %g\n",
2279	i, iColumn, numberThisDown, object->downEstimate(), numberThisUp, object->upEstimate(),
2280	infeasibility, sort[numberToDo], saveSolution[iColumn]);
2281	}
2282	whichObject[numberToDo++] = i;
2283	} else {
2284	// for debug
2285	downEstimate[i] = -1.0;
2286	upEstimate[i] = -1.0;
2287	}
2288	}
2289	if (numberUnsatisfied_) {
2290	//if (probingInfo&&false)
2291	//printf("nunsat %d, %d probed, %d other 0-1\n",numberUnsatisfied_,
2292	// numberUnsatisProbed,numberUnsatisNotProbed);
2293	// some infeasibilities - go to next steps
2294	if (!canDoOneHot && hotstartSolution) {
2295	// switch off as not possible
2296	hotstartSolution = NULL;
2297	model->setHotstartSolution(NULL, NULL);
2298	usefulInfo.hotstartSolution_ = NULL;
2299	}
2300	break;
2301	} else if (!iPass) {
2302	// may just need resolve
2303	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
2304	double newObjValue = solver->getObjSense()*solver->getObjValue();
2305	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
2306	if (!solver->isProvenOptimal()) {
2307	// infeasible
2308	anyAction = -2;
2309	break;
2310	}
2311	// Double check looks OK - just look at rows with all integers
2312	if (model->allDynamic()) {
2313	double * solution = CoinCopyOfArray(saveSolution, numberColumns);
2314	for (int i = 0; i < numberColumns; i++) {
2315	if (model->isInteger(i))
2316	solution[i] = floor(solution[i] + 0.5);
2317	}
2318	int numberRows = solver->getNumRows();
2319	double * rowActivity = new double [numberRows];
2320	CoinZeroN(rowActivity, numberRows);
2321	solver->getMatrixByCol()->times(solution, rowActivity);
2322	//const double * element = model->solver()->getMatrixByCol()->getElements();
2323	const int * row = model->solver()->getMatrixByCol()->getIndices();
2324	const CoinBigIndex * columnStart = model->solver()->getMatrixByCol()->getVectorStarts();
2325	const int * columnLength = model->solver()->getMatrixByCol()->getVectorLengths();
2326	int nFree = 0;
2327	int nFreeNon = 0;
2328	int nFixedNon = 0;
2329	double mostAway = 0.0;
2330	int whichAway = -1;
2331	const double * columnLower = solver->getColLower();
2332	const double * columnUpper = solver->getColUpper();
2333	for (int i = 0; i < numberColumns; i++) {
2334	if (!model->isInteger(i)) {
2335	// mark rows as flexible
2336	CoinBigIndex start = columnStart[i];
2337	CoinBigIndex end = start + columnLength[i];
2338	for (CoinBigIndex j = start; j < end; j++) {
2339	int iRow = row[j];
2340	rowActivity[iRow] = COIN_DBL_MAX;
2341	}
2342	} else if (columnLower[i] < columnUpper[i]) {
2343	double solutionValue = saveSolution[i];
2344	if (fabs(solution[i] - solutionValue) >
2345	integerTolerance &&
2346	(solutionValue - columnLower[i]) >
2347	integerTolerance &&
2348	(columnUpper[i] - solutionValue) >
2349	integerTolerance) {
2350	nFreeNon++;
2351	if (fabs(solution[i] - saveSolution[i]) > mostAway) {
2352	mostAway = fabs(solution[i] - saveSolution[i]);
2353	whichAway = i;
2354	}
2355	} else {
2356	nFree++;
2357	}
2358	} else if (solution[i] != saveSolution[i]) {
2359	nFixedNon++;
2360	}
2361	}
2362	const double * lower = solver->getRowLower();
2363	const double * upper = solver->getRowUpper();
2364	bool satisfied = true;
2365	for (int i = 0; i < numberRows; i++) {
2366	double value = rowActivity[i];
2367	if (value != COIN_DBL_MAX) {
2368	if (value > upper[i] + 1.0e-5 \|\| value < lower[i] - 1.0e-5) {
2369	satisfied = false;
2370	}
2371	}
2372	}
2373	delete [] rowActivity;
2374	if (!satisfied) {
2375	#ifdef CLP_INVESTIGATE
2376	printf("%d free ok %d free off target %d fixed off target\n",
2377	nFree, nFreeNon, nFixedNon);
2378	#endif
2379	if (nFreeNon) {
2380	// try branching on these
2381	delete branch_;
2382	for (int i = 0; i < numberObjects; i++) {
2383	OsiObject * object = model->modifiableObject(i);
2384	CbcSimpleIntegerDynamicPseudoCost * obj =
2385	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
2386	assert (obj);
2387	int iColumn = obj->columnNumber();
2388	if (iColumn == whichAway) {
2389	int preferredWay = (saveSolution[iColumn] > solution[iColumn])
2390	? -1 : +1;
2391	usefulInfo.integerTolerance_ = 0.0;
2392	branch_ = obj->createCbcBranch(solver, &usefulInfo, preferredWay);
2393	break;
2394	}
2395	}
2396	anyAction = 0;
2397	break;
2398	}
2399	}
2400	delete [] solution;
2401	}
2402	} else if (iPass == 1) {
2403	// looks like a solution - get paranoid
2404	bool roundAgain = false;
2405	// get basis
2406	CoinWarmStartBasis * ws = dynamic_cast<CoinWarmStartBasis*>(solver->getWarmStart());
2407	if (!ws)
2408	break;
2409	double tolerance;
2410	solver->getDblParam(OsiPrimalTolerance, tolerance);
2411	for (i = 0; i < numberColumns; i++) {
2412	double value = saveSolution[i];
2413	if (value < lower[i] - tolerance) {
2414	saveSolution[i] = lower[i];
2415	roundAgain = true;
2416	ws->setStructStatus(i, CoinWarmStartBasis::atLowerBound);
2417	} else if (value > upper[i] + tolerance) {
2418	saveSolution[i] = upper[i];
2419	roundAgain = true;
2420	ws->setStructStatus(i, CoinWarmStartBasis::atUpperBound);
2421	}
2422	}
2423	if (roundAgain) {
2424	// restore basis
2425	solver->setWarmStart(ws);
2426	solver->setColSolution(saveSolution);
2427	delete ws;
2428	bool takeHint;
2429	OsiHintStrength strength;
2430	solver->getHintParam(OsiDoDualInResolve, takeHint, strength);
2431	solver->setHintParam(OsiDoDualInResolve, false, OsiHintDo) ;
2432	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
2433	double newObjValue = solver->getObjSense()*solver->getObjValue();
2434	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
2435	solver->setHintParam(OsiDoDualInResolve, takeHint, strength) ;
2436	if (!solver->isProvenOptimal()) {
2437	// infeasible
2438	anyAction = -2;
2439	break;
2440	}
2441	} else {
2442	delete ws;
2443	break;
2444	}
2445	}
2446	}
2447	if (anyAction == -2) {
2448	break;
2449	}
2450	// skip if solution
2451	if (!numberUnsatisfied_)
2452	break;
2453	int skipAll = (numberNotTrusted == 0 \|\| numberToDo == 1) ? 1 : 0;
2454	bool doneHotStart = false;
2455	//DEPRECATED_STRATEGYint searchStrategy = saveSearchStrategy>=0 ? (saveSearchStrategy%10) : -1;
2456	int searchStrategy = model->searchStrategy();
2457	// But adjust depending on ratio of iterations
2458	if (searchStrategy > 0) {
2459	if (numberBeforeTrust >= /5/ 10 && numberBeforeTrust <= 10) {
2460	if (searchStrategy != 2) {
2461	assert (searchStrategy == 1);
2462	if (depth_ > 5) {
2463	int numberIterations = model->getIterationCount();
2464	int numberStrongIterations = model->numberStrongIterations();
2465	if (numberStrongIterations > numberIterations + 10000) {
2466	searchStrategy = 2;
2467	skipAll = 1;
2468	} else if (numberStrongIterations*4 + 1000 < numberIterations) {
2469	searchStrategy = 3;
2470	skipAll = 0;
2471	}
2472	} else {
2473	searchStrategy = 3;
2474	skipAll = 0;
2475	}
2476	}
2477	}
2478	}
2479	// worth trying if too many times
2480	// Save basis
2481	CoinWarmStart * ws = NULL;
2482	// save limit
2483	int saveLimit = 0;
2484	solver->getIntParam(OsiMaxNumIterationHotStart, saveLimit);
2485	if (!numberPassesLeft)
2486	skipAll = 1;
2487	if (!skipAll) {
2488	ws = solver->getWarmStart();
2489	int limit = 100;
2490	if (!saveStateOfSearch && saveLimit < limit && saveLimit == 100)
2491	solver->setIntParam(OsiMaxNumIterationHotStart, limit);
2492	}
2493	// Say which one will be best
2494	int whichChoice = 0;
2495	int bestChoice;
2496	if (iBestGot >= 0)
2497	bestChoice = iBestGot;
2498	else
2499	bestChoice = iBestNot;
2500	assert (bestChoice >= 0);
2501	// If we have hit max time don't do strong branching
2502	bool hitMaxTime = (model->getCurrentSeconds() >
2503	model->getDblParam(CbcModel::CbcMaximumSeconds));
2504	// also give up if we are looping round too much
2505	if (hitMaxTime \|\| numberPassesLeft <= 0 \|\| useShadow == 2) {
2506	int iObject = whichObject[bestChoice];
2507	OsiObject * object = model->modifiableObject(iObject);
2508	int preferredWay;
2509	object->infeasibility(&usefulInfo, preferredWay);
2510	CbcObject * obj =
2511	dynamic_cast <CbcObject *>(object) ;
2512	assert (obj);
2513	branch_ = obj->createCbcBranch(solver, &usefulInfo, preferredWay);
2514	{
2515	CbcBranchingObject * branchObj =
2516	dynamic_cast <CbcBranchingObject *>(branch_) ;
2517	assert (branchObj);
2518	branchObj->way(preferredWay);
2519	}
2520	delete ws;
2521	ws = NULL;
2522	break;
2523	} else {
2524	// say do fast
2525	int easy = 1;
2526	if (!skipAll)
2527	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, &easy) ;
2528	int iDo;
2529	#define RESET_BOUNDS
2530	#ifdef RANGING
2531	bool useRanging = model->allDynamic() && !skipAll;
2532	if (useRanging) {
2533	double currentObjective = solver->getObjValue() * solver->getObjSense();
2534	double gap = cutoff - currentObjective;
2535	// relax a bit
2536	gap *= 1.0000001;
2537	gap = CoinMax(1.0e-5, gap);
2538	// off penalties if too much
2539	double needed = neededPenalties;
2540	needed *= numberRows;
2541	if (numberNodes) {
2542	if (needed > 1.0e6) {
2543	neededPenalties = 0;
2544	} else if (gap < 1.0e5) {
2545	// maybe allow some not needed
2546	int extra = static_cast<int> ((1.0e6 - needed) / numberRows);
2547	int nStored = numberObjects - optionalPenalties;
2548	extra = CoinMin(extra, nStored);
2549	for (int i = 0; i < extra; i++) {
2550	objectMark[neededPenalties] = objectMark[optionalPenalties+i];
2551	which[neededPenalties++] = which[optionalPenalties+i];;
2552	}
2553	}
2554	}
2555	if (osiclp && neededPenalties) {
2556	assert (!doneHotStart);
2557	xPen += neededPenalties;
2558	which--;
2559	which[0] = neededPenalties;
2560	osiclp->passInRanges(which);
2561	// Mark hot start and get ranges
2562	if (kPass) {
2563	// until can work out why solution can go funny
2564	int save = osiclp->specialOptions();
2565	osiclp->setSpecialOptions(save \| 256);
2566	solver->markHotStart();
2567	#ifdef RESET_BOUNDS
2568	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
2569	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
2570	#endif
2571	osiclp->setSpecialOptions(save);
2572	} else {
2573	solver->markHotStart();
2574	#ifdef RESET_BOUNDS
2575	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
2576	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
2577	#endif
2578	}
2579	doneHotStart = true;
2580	xMark++;
2581	kPass++;
2582	osiclp->passInRanges(NULL);
2583	const double * downCost = osiclp->upRange();
2584	const double * upCost = osiclp->downRange();
2585	bool problemFeasible = true;
2586	int numberFixed = 0;
2587	for (int i = 0; i < neededPenalties; i++) {
2588	int j = objectMark[i];
2589	int iObject = whichObject[j];
2590	OsiObject * object = model->modifiableObject(iObject);
2591	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
2592	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
2593	// Use this object's numberBeforeTrust
2594	int numberBeforeTrustThis = dynamicObject->numberBeforeTrust();
2595	int iSequence = dynamicObject->columnNumber();
2596	double value = saveSolution[iSequence];
2597	value -= floor(value);
2598	double upPenalty = CoinMin(upCost[i], 1.0e110) * (1.0 - value);
2599	double downPenalty = CoinMin(downCost[i], 1.0e110) * value;
2600	int numberThisDown = dynamicObject->numberTimesDown();
2601	int numberThisUp = dynamicObject->numberTimesUp();
2602	if (!numberBeforeTrustThis) {
2603	// override
2604	downEstimate[iObject] = downPenalty;
2605	upEstimate[iObject] = upPenalty;
2606	double min1 = CoinMin(downEstimate[iObject],
2607	upEstimate[iObject]);
2608	double max1 = CoinMax(downEstimate[iObject],
2609	upEstimate[iObject]);
2610	min1 = 0.8 * min1 + 0.2 * max1;
2611	sort[j] = - min1;
2612	} else if (numberThisDown < numberBeforeTrustThis \|\|
2613	numberThisUp < numberBeforeTrustThis) {
2614	double invTrust = 1.0 / static_cast<double> (numberBeforeTrustThis);
2615	if (numberThisDown < numberBeforeTrustThis) {
2616	double fraction = numberThisDown * invTrust;
2617	downEstimate[iObject] = fraction * downEstimate[iObject] + (1.0 - fraction) * downPenalty;
2618	}
2619	if (numberThisUp < numberBeforeTrustThis) {
2620	double fraction = numberThisUp * invTrust;
2621	upEstimate[iObject] = fraction * upEstimate[iObject] + (1.0 - fraction) * upPenalty;
2622	}
2623	double min1 = CoinMin(downEstimate[iObject],
2624	upEstimate[iObject]);
2625	double max1 = CoinMax(downEstimate[iObject],
2626	upEstimate[iObject]);
2627	min1 = 0.8 * min1 + 0.2 * max1;
2628	min1 *= 10.0;
2629	if (!(numberThisDown + numberThisUp))
2630	min1 *= 100.0;
2631	sort[j] = - min1;
2632	}
2633	// seems unreliable
2634	if (false&&CoinMax(downPenalty, upPenalty) > gap) {
2635	COIN_DETAIL_PRINT(printf("gap %g object %d has down range %g, up %g\n",
2636	gap, i, downPenalty, upPenalty));
2637	//sort[j] -= 1.0e50; // make more likely to be chosen
2638	int number;
2639	if (downPenalty > gap) {
2640	number = dynamicObject->numberTimesDown();
2641	if (upPenalty > gap)
2642	problemFeasible = false;
2643	CbcBranchingObject * branch = dynamicObject->createCbcBranch(solver, &usefulInfo, 1);
2644	//branch->fix(solver,saveLower,saveUpper,1);
2645	delete branch;
2646	} else {
2647	number = dynamicObject->numberTimesUp();
2648	CbcBranchingObject * branch = dynamicObject->createCbcBranch(solver, &usefulInfo, 1);
2649	//branch->fix(solver,saveLower,saveUpper,-1);
2650	delete branch;
2651	}
2652	if (number >= numberBeforeTrustThis)
2653	dynamicObject->setNumberBeforeTrust(CoinMin(number + 1,5*numberBeforeTrust));
2654	numberFixed++;
2655	}
2656	if (!numberNodes)
2657	COIN_DETAIL_PRINT(printf("%d pen down ps %g -> %g up ps %g -> %g\n",
2658	iObject, downPenalty, downPenalty, upPenalty, upPenalty));
2659	}
2660	if (numberFixed && problemFeasible) {
2661	assert(doneHotStart);
2662	solver->unmarkHotStart();
2663	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
2664	#ifdef CHECK_DEBUGGER_PATH
2665	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
2666	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
2667	if (!debugger) {
2668	printf("Strong branching down on %d went off optimal path\n",iObject);
2669	abort();
2670	}
2671	}
2672	#endif
2673	double newObjValue = solver->getObjSense()*solver->getObjValue();
2674	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
2675	solver->markHotStart();
2676	#ifdef RESET_BOUNDS
2677	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
2678	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
2679	#endif
2680	problemFeasible = solver->isProvenOptimal();
2681	}
2682	if (!problemFeasible) {
2683	COIN_DETAIL_PRINT(fprintf(stdout, "both ways infeas on ranging - code needed\n"));
2684	anyAction = -2;
2685	if (!choiceObject) {
2686	delete choice.possibleBranch;
2687	choice.possibleBranch = NULL;
2688	}
2689	//printf("Both infeasible for choice %d sequence %d\n",i,
2690	// model->object(choice.objectNumber)->columnNumber());
2691	// Delete the snapshot
2692	solver->unmarkHotStart();
2693	// back to normal
2694	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, NULL) ;
2695	// restore basis
2696	solver->setWarmStart(ws);
2697	doneHotStart = false;
2698	delete ws;
2699	ws = NULL;
2700	break;
2701	}
2702	}
2703	}
2704	#endif /* RANGING */
2705	{
2706	int numberIterations = model->getIterationCount();
2707	//numberIterations += (model->numberExtraIterations()>>2);
2708	const int * strongInfo = model->strongInfo();
2709	//int numberDone = strongInfo[0]-strongInfo[3];
2710	int numberFixed = strongInfo[1] - strongInfo[4];
2711	int numberInfeasible = strongInfo[2] - strongInfo[5];
2712	assert (!strongInfo[3]);
2713	assert (!strongInfo[4]);
2714	assert (!strongInfo[5]);
2715	int numberStrongIterations = model->numberStrongIterations();
2716	int numberRows = solver->getNumRows();
2717	if (numberStrongIterations > numberIterations + CoinMin(100, 10*numberRows) && depth_ >= 4 && numberNodes > 100) {
2718	if (20numberInfeasible + 4numberFixed < numberNodes) {
2719	// Say never do
2720	if (numberBeforeTrust == 5)
2721	skipAll = -1;
2722	}
2723	}
2724	}
2725	// make sure best will be first
2726	if (iBestGot >= 0)
2727	sort[iBestGot] = -COIN_DBL_MAX;
2728	// Actions 0 - exit for repeat, 1 resolve and try old choice,2 exit for continue
2729	if (anyAction)
2730	numberToDo = 0; // skip as we will be trying again
2731	// Sort
2732	CoinSort_2(sort, sort + numberToDo, whichObject);
2733	// Change in objective opposite infeasible
2734	double worstFeasible = 0.0;
2735	// Just first if strong off
2736	if (!numberStrong)
2737	numberToDo = CoinMin(numberToDo, 1);
2738	if (searchStrategy == 2)
2739	numberToDo = CoinMin(numberToDo, 20);
2740	iDo = 0;
2741	int saveLimit2;
2742	solver->getIntParam(OsiMaxNumIterationHotStart, saveLimit2);
2743	int numberTest = numberNotTrusted > 0 ? numberStrong : (numberStrong + 1) / 2;
2744	if (searchStrategy == 3) {
2745	// Previously decided we need strong
2746	numberTest = numberStrong;
2747	}
2748	// Try nearly always off
2749	if (skipAll >= 0) {
2750	if (searchStrategy < 2) {
2751	//if ((numberNodes%20)!=0) {
2752	if ((model->specialOptions()&8) == 0) {
2753	numberTest = 0;
2754	}
2755	//} else {
2756	//numberTest=2*numberStrong;
2757	//skipAll=0;
2758	//}
2759	}
2760	} else {
2761	// Just take first
2762	numberTest = 1;
2763	}
2764	int testDepth = (skipAll >= 0) ? 8 : 4;
2765	if (depth_ < testDepth && numberStrong) {
2766	if (searchStrategy != 2) {
2767	int numberRows = solver->getNumRows();
2768	// whether to do this or not is important - think
2769	if (numberRows < 300 \|\| numberRows + numberColumns < 2500) {
2770	if (depth_ < 7)
2771	numberStrong = CoinMin(3 * numberStrong, numberToDo);
2772	if (!depth_)
2773	numberStrong = CoinMin(6 * numberStrong, numberToDo);
2774	}
2775	numberTest = numberStrong;
2776	skipAll = 0;
2777	}
2778	}
2779	// Do at least 5 strong
2780	if (numberColumns < 1000 && (depth_ < 15 \|\| numberNodes < 1000000))
2781	numberTest = CoinMax(numberTest, 5);
2782	if ((model->specialOptions()&8) == 0) {
2783	if (skipAll) {
2784	numberTest = 0;
2785	}
2786	} else {
2787	// do 5 as strong is fixing
2788	numberTest = CoinMax(numberTest, 5);
2789	}
2790	// see if switched off
2791	if (skipAll < 0) {
2792	numberTest = 0;
2793	}
2794	int realMaxHotIterations = 999999;
2795	if (skipAll < 0)
2796	numberToDo = 1;
2797	strongType=0;
2798	#ifdef DO_ALL_AT_ROOT
2799	if (model->strongStrategy()) {
2800	int iStrategy=model->strongStrategy();
2801	int kDepth = iStrategy/100;
2802	if (kDepth)
2803	iStrategy -= 100*kDepth;
2804	else
2805	kDepth=5;
2806	double objValue = solver->getObjSense()*solver->getObjValue();
2807	double bestPossible = model->getBestPossibleObjValue();
2808	bestPossible += 1.0e-7*(1.0+fabs(bestPossible));
2809	int jStrategy = iStrategy/10;
2810	if (jStrategy) {
2811	if ((jStrategy&1)!=0&&!depth_)
2812	strongType=2;
2813	else if ((jStrategy&2)!=0&&depth_<=kDepth)
2814	strongType=2;
2815	else if ((jStrategy&4)!=0&&objValue<bestPossible)
2816	strongType=2;
2817	iStrategy-=10*jStrategy;
2818	}
2819	if (!strongType) {
2820	if ((iStrategy&1)!=0&&!depth_)
2821	strongType=1;
2822	else if ((iStrategy&2)!=0&&depth_<=kDepth)
2823	strongType=1;
2824	else if ((iStrategy&4)!=0&&objValue<bestPossible)
2825	strongType=1;
2826	}
2827	saveNumberToDo=numberToDo;
2828	if (strongType==2) {
2829	// add in satisfied
2830	const int * integerVariable = model->integerVariable();
2831	int numberIntegers = model->numberIntegers();
2832	if (numberIntegers==numberObjects) {
2833	numberToDo=0;
2834	for (int i=0;i<numberIntegers;i++) {
2835	int iColumn=integerVariable[i];
2836	if (saveUpper[iColumn]>saveLower[iColumn]) {
2837	whichObject [numberToDo++]=i;
2838	}
2839	}
2840	saveSatisfiedVariables=numberToDo-saveNumberToDo;
2841	} else {
2842	strongType=1;
2843	}
2844	}
2845	if (strongType) {
2846	numberTest = numberToDo;
2847	numberStrong=numberToDo;
2848	skipAll=0;
2849	searchStrategy=0;
2850	solver->setIntParam(OsiMaxNumIterationHotStart, 100000);
2851	//printf("Strong branching type %d\n",strongType);
2852	}
2853	}
2854	#endif
2855	#ifdef COIN_HAS_NTY
2856	const int * orbits = NULL;
2857	#endif
2858	#ifdef COIN_HAS_NTY
2859	if (orbitOption==2 /* was >1*/) {
2860	CbcSymmetry * symmetryInfo = model->symmetryInfo();
2861	CbcNodeInfo * infoX = lastNode ? lastNode->nodeInfo() : NULL;
2862	bool worthTrying = false;
2863	if (infoX) {
2864	CbcNodeInfo * info = infoX;
2865	for (int i=0;i<NTY_BAD_DEPTH;i++) {
2866	if (!info->parent()) {
2867	worthTrying = true;
2868	break;
2869	}
2870	info = info->parent();
2871	if (info->symmetryWorked()) {
2872	worthTrying = true;
2873	break;
2874	}
2875	}
2876	} else {
2877	worthTrying=true;
2878	}
2879	if (symmetryInfo && worthTrying) {
2880	symmetryInfo->ChangeBounds(solver->getColLower(),
2881	solver->getColUpper(),
2882	solver->getNumCols(),false);
2883	symmetryInfo->Compute_Symmetry();
2884	symmetryInfo->fillOrbits();
2885	orbits = symmetryInfo->whichOrbit();
2886	int iColumn=-1;
2887	if (orbits && symmetryInfo->numberUsefulOrbits()) {
2888	bool doBranch=true;
2889	int numberUsefulOrbits = symmetryInfo->numberUsefulOrbits();
2890	if (numberUsefulOrbits<2) {
2891	assert (numberUsefulOrbits);
2892	double largest=-1.0;
2893	for (int i=0;i<numberColumns;i++) {
2894	if (orbits[i]>=0) {
2895	if (saveSolution[i]>largest) {
2896	largest=saveSolution[i];
2897	iColumn=i;
2898	}
2899	}
2900	}
2901	} else {
2902	#if COIN_HAS_NTY2 == 1
2903	// take largest
2904	int iOrbit=symmetryInfo->largestOrbit(solver->getColLower(),
2905	solver->getColUpper());
2906	double largest=-1.0;
2907	for (int i=0;i<numberColumns;i++) {
2908	if (orbits[i]==iOrbit) {
2909	if (saveSolution[i]>largest) {
2910	largest=saveSolution[i];
2911	iColumn=i;
2912	}
2913	}
2914	}
2915	#endif
2916	if (orbitOption==2) {
2917	// strong
2918	int nDo=0;
2919	const double * lower = solver->getColLower();
2920	const double * upper = solver->getColUpper();
2921	const int * integerVariable = model->integerVariable();
2922	for (int iOrbit = 0; iOrbit < numberUsefulOrbits; iOrbit++) {
2923	double distance=1.0;
2924	int iColumn = -1;
2925	int numberIntegers = model->numberIntegers();
2926	for (int j=0;j<numberIntegers;j++) {
2927	int i=integerVariable[j];
2928	if (orbits[i]==iOrbit &&lower[i]==0.0&&upper[i]==1.0) {
2929	double away = fabs(saveSolution[i]-0.5);
2930	if (away<distance&&away<0.4999) {
2931	distance=away;
2932	iColumn=j;
2933	}
2934	}
2935	}
2936	if (iColumn>=0)
2937	whichObject[nDo++]=iColumn;
2938	}
2939	if (nDo)
2940	numberToDo=nDo;
2941	doBranch=false;
2942	} else if (orbitOption==3) {
2943	// subset
2944	int nDo=0;
2945	for (int iDo = 0; iDo < numberToDo; iDo++) {
2946	int iObject = whichObject[iDo];
2947	OsiObject * object = model->modifiableObject(iObject);
2948	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
2949	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
2950	int iColumn = dynamicObject ? dynamicObject->columnNumber() : -1;
2951	if (iColumn<0\|\|orbits[iColumn]>=0)
2952	whichObject[nDo++]=whichObject[iDo];
2953	}
2954	assert(nDo);
2955	//printf("nDo %d\n",nDo);
2956	numberToDo=nDo;
2957	doBranch=false;
2958	/* need NULL as if two in same orbit and strong branching fixes
2959	then we may be in trouble.
2960	Strong option should be OK as only one in set done.
2961	*/
2962	orbits=NULL;
2963	}
2964	}
2965	if(doBranch) {
2966	orbitOption=0;
2967	branch_ = new CbcOrbitalBranchingObject(model,iColumn,1,0,NULL);
2968	if (infoX)
2969	infoX->setSymmetryWorked();
2970	numberToDo=0;
2971	}
2972	}
2973	}
2974	}
2975	#endif
2976	for ( iDo = 0; iDo < numberToDo; iDo++) {
2977	int iObject = whichObject[iDo];
2978	OsiObject * object = model->modifiableObject(iObject);
2979	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
2980	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
2981	int iColumn = dynamicObject ? dynamicObject->columnNumber() : numberColumns + iObject;
2982	int preferredWay;
2983	double infeasibility = object->infeasibility(&usefulInfo, preferredWay);
2984	bool feasibleSolution=false;
2985	double predictedChange=0.0;
2986	// may have become feasible
2987	if (!infeasibility) {
2988	if(strongType!=2\|\|solver->getColLower()[iColumn]==solver->getColUpper()[iColumn])
2989	continue;
2990	}
2991	#ifndef NDEBUG
2992	if (iColumn < numberColumns) {
2993	const double * solution = model->testSolution();
2994	assert (saveSolution[iColumn] == solution[iColumn]);
2995	}
2996	#endif
2997	CbcSimpleInteger * obj =
2998	dynamic_cast <CbcSimpleInteger *>(object) ;
2999	if (obj) {
3000	if (choiceObject) {
3001	obj->fillCreateBranch(choiceObject, &usefulInfo, preferredWay);
3002	choiceObject->setObject(dynamicObject);
3003	} else {
3004	choice.possibleBranch = obj->createCbcBranch(solver, &usefulInfo, preferredWay);
3005	}
3006	} else {
3007	CbcObject * obj =
3008	dynamic_cast <CbcObject *>(object) ;
3009	assert (obj);
3010	choice.possibleBranch = obj->createCbcBranch(solver, &usefulInfo, preferredWay);
3011	}
3012	// Save which object it was
3013	choice.objectNumber = iObject;
3014	choice.numIntInfeasUp = numberUnsatisfied_;
3015	choice.numIntInfeasDown = numberUnsatisfied_;
3016	if (strongType!=2) {
3017	choice.upMovement = upEstimate[iObject];
3018	choice.downMovement = downEstimate[iObject];
3019	} else {
3020	choice.upMovement = 0.1;
3021	choice.downMovement = 0.1;
3022	}
3023	assert (choice.upMovement >= 0.0);
3024	assert (choice.downMovement >= 0.0);
3025	choice.fix = 0; // say not fixed
3026	// see if can skip strong branching
3027	int canSkip = choice.possibleBranch->fillStrongInfo(choice);
3028	if ((numberTest <= 0 \|\| skipAll)) {
3029	if (iDo > 20) {
3030	if (!choiceObject) {
3031	delete choice.possibleBranch;
3032	choice.possibleBranch = NULL;
3033	}
3034	break; // give up anyway
3035	}
3036	}
3037	if (model->messageHandler()->logLevel() > 3 && numberBeforeTrust && dynamicObject)
3038	dynamicObject->print(1, choice.possibleBranch->value());
3039	if (strongType)
3040	canSkip=0;
3041	if (skipAll < 0)
3042	canSkip = 1;
3043	if (!canSkip) {
3044	if (!doneHotStart) {
3045	// Mark hot start
3046	doneHotStart = true;
3047	solver->markHotStart();
3048	#ifdef RESET_BOUNDS
3049	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
3050	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
3051	#endif
3052	if (!solver->isProvenOptimal()) {
3053	skipAll=-2;
3054	canSkip = 1;
3055	}
3056	xMark++;
3057	}
3058	}
3059	if (!canSkip) {
3060	numberTest--;
3061	// just do a few
3062	if (searchStrategy == 2)
3063	solver->setIntParam(OsiMaxNumIterationHotStart, 10);
3064	double objectiveChange ;
3065	double newObjectiveValue = 1.0e100;
3066	int j;
3067	#ifdef COIN_HAS_CLP
3068	int saveMaxHotIts=0;
3069	int saveOsiClpOptions=0;
3070	if (osiclp && goToEndInStrongBranching) {
3071	/* How dogged to be in strong branching
3072	0 - default
3073	1 - go to end on first time
3074	2 - always go to end
3075	*/
3076	osiclp->getIntParam(OsiMaxNumIterationHotStart, saveMaxHotIts);
3077	saveOsiClpOptions=osiclp->specialOptions();
3078	if (goToEndInStrongBranching==2 \|\|
3079	dynamicObject->numberTimesBranched()==0) {
3080	osiclp->setIntParam(OsiMaxNumIterationHotStart,
3081	10*(osiclp->getNumRows()+numberColumns));
3082	osiclp->setSpecialOptions(saveOsiClpOptions & (~32));
3083	}
3084	}
3085	#endif
3086	// status is 0 finished, 1 infeasible and other
3087	int iStatus;
3088	/*
3089	Try the down direction first. (Specify the initial branching alternative as
3090	down with a call to way(-1). Each subsequent call to branch() performs the
3091	specified branch and advances the branch object state to the next branch
3092	alternative.)
3093	*/
3094	choice.possibleBranch->way(-1) ;
3095	predictedChange = choice.possibleBranch->branch() ;
3096	#ifdef COIN_HAS_NTY
3097	if (orbits) {
3098	// can fix all in orbit
3099	int fixOrbit = orbits[iObject];
3100	if (fixOrbit>=0) {
3101	//printf("fixing all in orbit %d for column %d\n",fixOrbit,iObject);
3102	for (int i=0;i<numberColumns;i++) {
3103	if (orbits[i]==fixOrbit)
3104	solver->setColUpper(i,0.0);
3105	}
3106	}
3107	}
3108	#endif
3109	solver->solveFromHotStart() ;
3110	bool needHotStartUpdate = false;
3111	numberStrongDone++;
3112	numberStrongIterations += solver->getIterationCount();
3113	/*
3114	We now have an estimate of objective degradation that we can use for strong
3115	branching. If we're over the cutoff, the variable is monotone up.
3116	If we actually made it to optimality, check for a solution, and if we have
3117	a good one, call setBestSolution to process it. Note that this may reduce the
3118	cutoff, so we check again to see if we can declare this variable monotone.
3119	*/
3120	if (solver->isProvenOptimal())
3121	iStatus = 0; // optimal
3122	else if (solver->isIterationLimitReached()
3123	&& !solver->isDualObjectiveLimitReached()) {
3124	iStatus = 2; // unknown
3125	} else {
3126	iStatus = 1; // infeasible
3127	#ifdef CONFLICT_CUTS
3128	#undef CONFLICT_CUTS
3129	//#define CONFLICT_CUTS 2
3130	#endif
3131	#ifdef CONFLICT_CUTS
3132	# ifdef COIN_HAS_CLP
3133	if (osiclp&&(model->moreSpecialOptions()&4194304)!=0) {
3134	const CbcFullNodeInfo * topOfTree =
3135	model->topOfTree();
3136	if (topOfTree) {
3137	#if CONFLICT_CUTS==2
3138	OsiRowCut * cut = osiclp->smallModelCut(topOfTree->lower(),
3139	topOfTree->upper(),
3140	model->numberRowsAtContinuous(),
3141	model->whichGenerator());
3142	#else
3143	OsiRowCut * cut = osiclp->modelCut(topOfTree->lower(),
3144	topOfTree->upper(),
3145	model->numberRowsAtContinuous(),
3146	model->whichGenerator(),0);
3147	#endif
3148	if (cut) {
3149	if (model->messageHandler()->logLevel() > 1)
3150	printf("Conflict cut found in strong branching (%d elements)\n",
3151	cut->row().getNumElements());
3152	//cut->print();
3153	if ((model->specialOptions()&1) != 0) {
3154	const OsiRowCutDebugger *debugger = model->continuousSolver()->getRowCutDebugger() ;
3155	if (debugger) {
3156	if (debugger->invalidCut(*cut)) {
3157	model->continuousSolver()->applyRowCuts(1,cut);
3158	model->continuousSolver()->writeMps("bad");
3159	}
3160	CoinAssert (!debugger->invalidCut(*cut));
3161	}
3162	}
3163	model->makeGlobalCut(cut) ;
3164	}
3165	}
3166	}
3167	#endif
3168	#endif
3169	}
3170	// say infeasible if branch says so
3171	if (predictedChange==COIN_DBL_MAX)
3172	iStatus=1;
3173	if (iStatus != 2 && solver->getIterationCount() >
3174	realMaxHotIterations)
3175	numberUnfinished++;
3176	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
3177	choice.numItersDown = solver->getIterationCount();
3178	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
3179	// Update branching information if wanted
3180	CbcBranchingObject * cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch);
3181	if (cbcobj) {
3182	CbcObject * object = cbcobj->object();
3183	assert (object) ;
3184	CbcObjectUpdateData update = object->createUpdateInformation(solver, this, cbcobj);
3185	update.objectNumber_ = choice.objectNumber;
3186	model->addUpdateInformation(update);
3187	} else {
3188	decision->updateInformation( solver, this);
3189	}
3190	if (!iStatus) {
3191	choice.finishedDown = true ;
3192	if (newObjectiveValue >= cutoff) {
3193	objectiveChange = 1.0e100; // say infeasible
3194	numberStrongInfeasible++;
3195	} else {
3196	#define CBCNODE_TIGHTEN_BOUNDS
3197	#ifdef CBCNODE_TIGHTEN_BOUNDS
3198	// Can we tighten bounds?
3199	if (iColumn < numberColumns && cutoff < 1.0e20
3200	&& objectiveChange > 1.0e-5) {
3201	double value = saveSolution[iColumn];
3202	double down = value - floor(value-integerTolerance);
3203	double changePer = objectiveChange / (down + 1.0e-7);
3204	double distance = (cutoff - objectiveValue_) / changePer;
3205	distance += 1.0e-3;
3206	if (distance < 5.0) {
3207	double newLower = ceil(value - distance);
3208	if (newLower > saveLower[iColumn]) {
3209	//printf("Could increase lower bound on %d from %g to %g\n",
3210	// iColumn,saveLower[iColumn],newLower);
3211	saveLower[iColumn] = newLower;
3212	solver->setColLower(iColumn, newLower);
3213	}
3214	}
3215	}
3216	#endif
3217	// See if integer solution
3218	feasibleSolution =
3219	model->feasibleSolution(choice.numIntInfeasDown,
3220	choice.numObjInfeasDown);
3221	if (feasibleSolution
3222	&& model->problemFeasibility()->feasible(model, -1) >= 0) {
3223	if (auxiliaryInfo->solutionAddsCuts()) {
3224	needHotStartUpdate = true;
3225	solver->unmarkHotStart();
3226	}
3227	model->setLogLevel(saveLogLevel);
3228	model->setBestSolution(CBC_STRONGSOL,
3229	newObjectiveValue,
3230	solver->getColSolution()) ;
3231	if (needHotStartUpdate) {
3232	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3233	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
3234	objectiveValue_ = CoinMax(objectiveValue_,newObjectiveValue);
3235	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
3236	model->feasibleSolution(choice.numIntInfeasDown,
3237	choice.numObjInfeasDown);
3238	}
3239	model->setLastHeuristic(NULL);
3240	model->incrementUsed(solver->getColSolution());
3241	cutoff = model->getCutoff();
3242	if (newObjectiveValue >= cutoff) { // new cutoff
3243	objectiveChange = 1.0e100 ;
3244	numberStrongInfeasible++;
3245	}
3246	}
3247	}
3248	} else if (iStatus == 1) {
3249	objectiveChange = 1.0e100 ;
3250	numberStrongInfeasible++;
3251	} else {
3252	// Can't say much as we did not finish
3253	choice.finishedDown = false ;
3254	numberUnfinished++;
3255	}
3256	choice.downMovement = objectiveChange ;
3257
3258	// restore bounds
3259	for ( j = 0; j < numberColumns; j++) {
3260	if (saveLower[j] != lower[j])
3261	solver->setColLower(j, saveLower[j]);
3262	if (saveUpper[j] != upper[j])
3263	solver->setColUpper(j, saveUpper[j]);
3264	}
3265	if (needHotStartUpdate) {
3266	needHotStartUpdate = false;
3267	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3268	#ifdef CHECK_DEBUGGER_PATH
3269	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3270	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3271	if (!debugger) {
3272	printf("Strong branching down on %d went off optimal path\n",iObject);
3273	model->solver()->writeMps("query");
3274	abort();
3275	}
3276	}
3277	#endif
3278	double newObjValue = solver->getObjSense()*solver->getObjValue();
3279	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3280	//we may again have an integer feasible solution
3281	int numberIntegerInfeasibilities;
3282	int numberObjectInfeasibilities;
3283	if (model->feasibleSolution(
3284	numberIntegerInfeasibilities,
3285	numberObjectInfeasibilities)) {
3286	#ifdef BONMIN
3287	//In this case node has become integer feasible, let us exit the loop
3288	std::cout << "Node has become integer feasible" << std::endl;
3289	numberUnsatisfied_ = 0;
3290	break;
3291	#endif
3292	double objValue = solver->getObjValue();
3293	model->setLogLevel(saveLogLevel);
3294	model->setBestSolution(CBC_STRONGSOL,
3295	objValue,
3296	solver->getColSolution()) ;
3297	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3298	double newObjValue = solver->getObjSense()*solver->getObjValue();
3299	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3300	cutoff = model->getCutoff();
3301	}
3302	solver->markHotStart();
3303	#ifdef RESET_BOUNDS
3304	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
3305	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
3306	#endif
3307	if (!solver->isProvenOptimal()) {
3308	skipAll=-2;
3309	canSkip = 1;
3310	}
3311	xMark++;
3312	}
3313	#if 0 //def DO_ALL_AT_ROOT
3314	if (strongType)
3315	printf("Down on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n",
3316	choice.objectNumber, iStatus, newObjectiveValue, choice.numItersDown,
3317	choice.downMovement, choice.finishedDown, choice.numIntInfeasDown,
3318	choice.numObjInfeasDown);
3319	#endif
3320
3321	// repeat the whole exercise, forcing the variable up
3322	predictedChange=choice.possibleBranch->branch();
3323	solver->solveFromHotStart() ;
3324	#ifdef COIN_HAS_CLP
3325	if (osiclp && goToEndInStrongBranching) {
3326	osiclp->setIntParam(OsiMaxNumIterationHotStart, saveMaxHotIts);
3327	osiclp->setSpecialOptions(saveOsiClpOptions);
3328	}
3329	#endif
3330	numberStrongDone++;
3331	numberStrongIterations += solver->getIterationCount();
3332	/*
3333	We now have an estimate of objective degradation that we can use for strong
3334	branching. If we're over the cutoff, the variable is monotone up.
3335	If we actually made it to optimality, check for a solution, and if we have
3336	a good one, call setBestSolution to process it. Note that this may reduce the
3337	cutoff, so we check again to see if we can declare this variable monotone.
3338	*/
3339	if (solver->isProvenOptimal())
3340	iStatus = 0; // optimal
3341	else if (solver->isIterationLimitReached()
3342	&& !solver->isDualObjectiveLimitReached()) {
3343	iStatus = 2; // unknown
3344	} else {
3345	iStatus = 1; // infeasible
3346	#ifdef CONFLICT_CUTS
3347	# ifdef COIN_HAS_CLP
3348	if (osiclp&&(model->moreSpecialOptions()&4194304)!=0) {
3349	const CbcFullNodeInfo * topOfTree =
3350	model->topOfTree();
3351	if (topOfTree) {
3352	#if CONFLICT_CUTS==2
3353	OsiRowCut * cut = osiclp->smallModelCut(topOfTree->lower(),
3354	topOfTree->upper(),
3355	model->numberRowsAtContinuous(),
3356	model->whichGenerator());
3357	#else
3358	OsiRowCut * cut = osiclp->modelCut(topOfTree->lower(),
3359	topOfTree->upper(),
3360	model->numberRowsAtContinuous(),
3361	model->whichGenerator(),0);
3362	#endif
3363	if (cut) {
3364	//printf("XXXXXX found conflict cut in strong branching\n");
3365	//cut->print();
3366	if ((model->specialOptions()&1) != 0) {
3367	const OsiRowCutDebugger *debugger = model->continuousSolver()->getRowCutDebugger() ;
3368	if (debugger) {
3369	if (debugger->invalidCut(*cut)) {
3370	model->continuousSolver()->applyRowCuts(1,cut);
3371	model->continuousSolver()->writeMps("bad");
3372	}
3373	CoinAssert (!debugger->invalidCut(*cut));
3374	}
3375	}
3376	model->makeGlobalCut(cut) ;
3377	}
3378	}
3379	}
3380	#endif
3381	#endif
3382	}
3383	// say infeasible if branch says so
3384	if (predictedChange==COIN_DBL_MAX)
3385	iStatus=1;
3386	if (iStatus != 2 && solver->getIterationCount() >
3387	realMaxHotIterations)
3388	numberUnfinished++;
3389	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
3390	choice.numItersUp = solver->getIterationCount();
3391	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
3392	// Update branching information if wanted
3393	cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch);
3394	if (cbcobj) {
3395	CbcObject * object = cbcobj->object();
3396	assert (object) ;
3397	CbcObjectUpdateData update = object->createUpdateInformation(solver, this, cbcobj);
3398	update.objectNumber_ = choice.objectNumber;
3399	model->addUpdateInformation(update);
3400	} else {
3401	decision->updateInformation( solver, this);
3402	}
3403	if (!iStatus) {
3404	choice.finishedUp = true ;
3405	if (newObjectiveValue >= cutoff) {
3406	objectiveChange = 1.0e100; // say infeasible
3407	numberStrongInfeasible++;
3408	} else {
3409	#ifdef CBCNODE_TIGHTEN_BOUNDS
3410	// Can we tighten bounds?
3411	if (iColumn < numberColumns && cutoff < 1.0e20
3412	&& objectiveChange > 1.0e-5) {
3413	double value = saveSolution[iColumn];
3414	double up = ceil(value+integerTolerance) - value;
3415	double changePer = objectiveChange / (up + 1.0e-7);
3416	double distance = (cutoff - objectiveValue_) / changePer;
3417	distance += 1.0e-3;
3418	if (distance < 5.0) {
3419	double newUpper = floor(value + distance);
3420	if (newUpper < saveUpper[iColumn]) {
3421	//printf("Could decrease upper bound on %d from %g to %g\n",
3422	// iColumn,saveUpper[iColumn],newUpper);
3423	saveUpper[iColumn] = newUpper;
3424	solver->setColUpper(iColumn, newUpper);
3425	}
3426	}
3427	}
3428	#endif
3429	// See if integer solution
3430	feasibleSolution =
3431	model->feasibleSolution(choice.numIntInfeasUp,
3432	choice.numObjInfeasUp);
3433	if (feasibleSolution
3434	&& model->problemFeasibility()->feasible(model, -1) >= 0) {
3435	#ifdef BONMIN
3436	std::cout << "Node has become integer feasible" << std::endl;
3437	numberUnsatisfied_ = 0;
3438	break;
3439	#endif
3440	if (auxiliaryInfo->solutionAddsCuts()) {
3441	needHotStartUpdate = true;
3442	solver->unmarkHotStart();
3443	}
3444	model->setLogLevel(saveLogLevel);
3445	model->setBestSolution(CBC_STRONGSOL,
3446	newObjectiveValue,
3447	solver->getColSolution()) ;
3448	if (choice.finishedDown) {
3449	double cutoff = model->getCutoff();
3450	double downObj = objectiveValue_
3451	+ choice.downMovement ;
3452	if (downObj >= cutoff) {
3453	choice.downMovement = 1.0e100 ;
3454	numberStrongInfeasible++;
3455	}
3456
3457	}
3458	if (needHotStartUpdate) {
3459	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3460	#ifdef CHECK_DEBUGGER_PATH
3461	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3462	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3463	if (!debugger) {
3464	printf("Strong branching up on %d went off optimal path\n",iObject);
3465	abort();
3466	}
3467	}
3468	#endif
3469	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
3470	objectiveValue_ = CoinMax(objectiveValue_,newObjectiveValue);
3471	objectiveChange = CoinMax(newObjectiveValue - objectiveValue_, 0.0);
3472	model->feasibleSolution(choice.numIntInfeasDown,
3473	choice.numObjInfeasDown);
3474	}
3475	model->setLastHeuristic(NULL);
3476	model->incrementUsed(solver->getColSolution());
3477	cutoff = model->getCutoff();
3478	if (newObjectiveValue >= cutoff) { // new cutoff
3479	objectiveChange = 1.0e100 ;
3480	numberStrongInfeasible++;
3481	}
3482	}
3483	}
3484	} else if (iStatus == 1) {
3485	objectiveChange = 1.0e100 ;
3486	numberStrongInfeasible++;
3487	} else {
3488	// Can't say much as we did not finish
3489	choice.finishedUp = false ;
3490	numberUnfinished++;
3491	}
3492	choice.upMovement = objectiveChange ;
3493
3494	// restore bounds
3495	for ( j = 0; j < numberColumns; j++) {
3496	if (saveLower[j] != lower[j])
3497	solver->setColLower(j, saveLower[j]);
3498	if (saveUpper[j] != upper[j])
3499	solver->setColUpper(j, saveUpper[j]);
3500	}
3501	if (needHotStartUpdate) {
3502	needHotStartUpdate = false;
3503	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3504	#ifdef CHECK_DEBUGGER_PATH
3505	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3506	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3507	if (!debugger) {
3508	printf("Strong branching up on %d went off optimal path\n",iObject);
3509	abort();
3510	}
3511	}
3512	#endif
3513	double newObjValue = solver->getObjSense()*solver->getObjValue();
3514	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3515	//we may again have an integer feasible solution
3516	int numberIntegerInfeasibilities;
3517	int numberObjectInfeasibilities;
3518	if (model->feasibleSolution(
3519	numberIntegerInfeasibilities,
3520	numberObjectInfeasibilities)) {
3521	double objValue = solver->getObjValue();
3522	model->setLogLevel(saveLogLevel);
3523	model->setBestSolution(CBC_STRONGSOL,
3524	objValue,
3525	solver->getColSolution()) ;
3526	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3527	#ifdef CHECK_DEBUGGER_PATH
3528	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3529	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3530	if (!debugger) {
3531	printf("Strong branching up on %d went off optimal path\n",iObject);
3532	abort();
3533	}
3534	}
3535	#endif
3536	double newObjValue = solver->getObjSense()*solver->getObjValue();
3537	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3538	cutoff = model->getCutoff();
3539	}
3540	solver->markHotStart();
3541	#ifdef RESET_BOUNDS
3542	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
3543	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
3544	#endif
3545	if (!solver->isProvenOptimal()) {
3546	skipAll=-2;
3547	canSkip = 1;
3548	}
3549	xMark++;
3550	}
3551
3552	#if 0 //def DO_ALL_AT_ROOT
3553	if (strongType)
3554	printf("Up on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n",
3555	choice.objectNumber, iStatus, newObjectiveValue, choice.numItersUp,
3556	choice.upMovement, choice.finishedUp, choice.numIntInfeasUp,
3557	choice.numObjInfeasUp);
3558	#endif
3559	}
3560
3561	solver->setIntParam(OsiMaxNumIterationHotStart, saveLimit2);
3562	/*
3563	End of evaluation for this candidate variable. Possibilities are:
3564	* Both sides below cutoff; this variable is a candidate for branching.
3565	* Both sides infeasible or above the objective cutoff: no further action
3566	here. Break from the evaluation loop and assume the node will be purged
3567	by the caller.
3568	* One side below cutoff: Install the branch (i.e., fix the variable). Break
3569	from the evaluation loop and assume the node will be reoptimised by the
3570	caller.
3571	*/
3572	// reset
3573	choice.possibleBranch->resetNumberBranchesLeft();
3574	if (choice.upMovement < 1.0e100) {
3575	if (choice.downMovement < 1.0e100) {
3576	// In case solution coming in was odd
3577	choice.upMovement = CoinMax(0.0, choice.upMovement);
3578	choice.downMovement = CoinMax(0.0, choice.downMovement);
3579	#if ZERO_ONE==2
3580	// branch on 0-1 first (temp)
3581	if (fabs(choice.possibleBranch->value()) < 1.0) {
3582	choice.upMovement *= ZERO_FAKE;
3583	choice.downMovement *= ZERO_FAKE;
3584	}
3585	#endif
3586	// feasible - see which best
3587	if (!canSkip) {
3588	if (model->messageHandler()->logLevel() > 3)
3589	printf("sort %g downest %g upest %g ", sort[iDo], downEstimate[iObject],
3590	upEstimate[iObject]);
3591	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
3592	<< iObject << iColumn
3593	<< choice.downMovement << choice.numIntInfeasDown
3594	<< choice.upMovement << choice.numIntInfeasUp
3595	<< choice.possibleBranch->value()
3596	<< CoinMessageEol;
3597	}
3598	int betterWay=0;
3599	// If was feasible (extra strong branching) skip
3600	if (infeasibility) {
3601	CbcBranchingObject * branchObj =
3602	dynamic_cast <CbcBranchingObject *>(branch_) ;
3603	if (branch_)
3604	assert (branchObj);
3605	betterWay = decision->betterBranch(choice.possibleBranch,
3606	branchObj,
3607	choice.upMovement,
3608	choice.numIntInfeasUp ,
3609	choice.downMovement,
3610	choice.numIntInfeasDown );
3611	}
3612	if (betterWay) {
3613	// C) create branching object
3614	if (choiceObject) {
3615	delete branch_;
3616	branch_ = choice.possibleBranch->clone();
3617	} else {
3618	delete branch_;
3619	branch_ = choice.possibleBranch;
3620	choice.possibleBranch = NULL;
3621	}
3622	{
3623	CbcBranchingObject * branchObj =
3624	dynamic_cast <CbcBranchingObject *>(branch_) ;
3625	assert (branchObj);
3626	//branchObj->way(preferredWay);
3627	branchObj->way(betterWay);
3628	}
3629	bestChoice = choice.objectNumber;
3630	whichChoice = iDo;
3631	if (numberStrong <= 1) {
3632	delete ws;
3633	ws = NULL;
3634	break;
3635	}
3636	} else {
3637	if (!choiceObject) {
3638	delete choice.possibleBranch;
3639	choice.possibleBranch = NULL;
3640	}
3641	if (iDo >= 2*numberStrong) {
3642	delete ws;
3643	ws = NULL;
3644	break;
3645	}
3646	if (!dynamicObject \|\| dynamicObject->numberTimesUp() > 1) {
3647	if (iDo - whichChoice >= numberStrong) {
3648	if (!choiceObject) {
3649	delete choice.possibleBranch;
3650	choice.possibleBranch = NULL;
3651	}
3652	break; // give up
3653	}
3654	} else {
3655	if (iDo - whichChoice >= 2*numberStrong) {
3656	delete ws;
3657	ws = NULL;
3658	if (!choiceObject) {
3659	delete choice.possibleBranch;
3660	choice.possibleBranch = NULL;
3661	}
3662	break; // give up
3663	}
3664	}
3665	}
3666	} else {
3667	// up feasible, down infeasible
3668	anyAction = -1;
3669	worstFeasible = CoinMax(worstFeasible, choice.upMovement);
3670	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
3671	<< iObject << iColumn
3672	<< choice.downMovement << choice.numIntInfeasDown
3673	<< choice.upMovement << choice.numIntInfeasUp
3674	<< choice.possibleBranch->value()
3675	<< CoinMessageEol;
3676	//printf("Down infeasible for choice %d sequence %d\n",i,
3677	// model->object(choice.objectNumber)->columnNumber());
3678	choice.fix = 1;
3679	numberToFix++;
3680	choice.possibleBranch->fix(solver, saveLower, saveUpper, 1);
3681	if (!choiceObject) {
3682	delete choice.possibleBranch;
3683	choice.possibleBranch = NULL;
3684	} else {
3685	//choiceObject = new CbcDynamicPseudoCostBranchingObject(*choiceObject);
3686	choice.possibleBranch = choiceObject;
3687	}
3688	assert(doneHotStart);
3689	solver->unmarkHotStart();
3690	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3691	#ifdef CHECK_DEBUGGER_PATH
3692	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3693	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3694	if (!debugger) {
3695	printf("Strong branching down on %d went off optimal path\n",iObject);
3696	abort();
3697	}
3698	}
3699	#endif
3700	double newObjValue = solver->getObjSense()*solver->getObjValue();
3701	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3702	bool goneInfeasible = (!solver->isProvenOptimal()\|\|solver->isDualObjectiveLimitReached());
3703	solver->markHotStart();
3704	#ifdef RESET_BOUNDS
3705	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
3706	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
3707	#endif
3708	if (!solver->isProvenOptimal()) {
3709	skipAll=-2;
3710	canSkip = 1;
3711	}
3712	xMark++;
3713	// may be infeasible (if other way stopped on iterations)
3714	if (goneInfeasible) {
3715	// neither side feasible
3716	anyAction = -2;
3717	if (!choiceObject) {
3718	delete choice.possibleBranch;
3719	choice.possibleBranch = NULL;
3720	}
3721	//printf("Both infeasible for choice %d sequence %d\n",i,
3722	// model->object(choice.objectNumber)->columnNumber());
3723	delete ws;
3724	ws = NULL;
3725	break;
3726	}
3727	}
3728	} else {
3729	if (choice.downMovement < 1.0e100) {
3730	// down feasible, up infeasible
3731	anyAction = -1;
3732	worstFeasible = CoinMax(worstFeasible, choice.downMovement);
3733	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
3734	<< iObject << iColumn
3735	<< choice.downMovement << choice.numIntInfeasDown
3736	<< choice.upMovement << choice.numIntInfeasUp
3737	<< choice.possibleBranch->value()
3738	<< CoinMessageEol;
3739	choice.fix = -1;
3740	numberToFix++;
3741	choice.possibleBranch->fix(solver, saveLower, saveUpper, -1);
3742	if (!choiceObject) {
3743	delete choice.possibleBranch;
3744	choice.possibleBranch = NULL;
3745	} else {
3746	//choiceObject = new CbcDynamicPseudoCostBranchingObject(*choiceObject);
3747	choice.possibleBranch = choiceObject;
3748	}
3749	assert(doneHotStart);
3750	solver->unmarkHotStart();
3751	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper);
3752	#ifdef CHECK_DEBUGGER_PATH
3753	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3754	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3755	if (!debugger) {
3756	printf("Strong branching down on %d went off optimal path\n",iObject);
3757	solver->writeMps("query");
3758	abort();
3759	}
3760	}
3761	#endif
3762	double newObjValue = solver->getObjSense()*solver->getObjValue();
3763	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3764	bool goneInfeasible = (!solver->isProvenOptimal()\|\|solver->isDualObjectiveLimitReached());
3765	solver->markHotStart();
3766	#ifdef RESET_BOUNDS
3767	memcpy(saveLower,solver->getColLower(),solver->getNumCols()*sizeof(double));
3768	memcpy(saveUpper,solver->getColUpper(),solver->getNumCols()*sizeof(double));
3769	#endif
3770	if (!solver->isProvenOptimal()) {
3771	skipAll=-2;
3772	canSkip = 1;
3773	}
3774	xMark++;
3775	// may be infeasible (if other way stopped on iterations)
3776	if (goneInfeasible) {
3777	// neither side feasible
3778	anyAction = -2;
3779	if (!choiceObject) {
3780	delete choice.possibleBranch;
3781	choice.possibleBranch = NULL;
3782	}
3783	delete ws;
3784	ws = NULL;
3785	break;
3786	}
3787	} else {
3788	// neither side feasible
3789	anyAction = -2;
3790	if (!choiceObject) {
3791	delete choice.possibleBranch;
3792	choice.possibleBranch = NULL;
3793	}
3794	delete ws;
3795	ws = NULL;
3796	break;
3797	}
3798	}
3799	// Check max time
3800	hitMaxTime = (model->getCurrentSeconds() >
3801	model->getDblParam(CbcModel::CbcMaximumSeconds));
3802	if (hitMaxTime) {
3803	// make sure rest are fast
3804	for ( int jDo = iDo + 1; jDo < numberToDo; jDo++) {
3805	int iObject = whichObject[iDo];
3806	OsiObject * object = model->modifiableObject(iObject);
3807	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
3808	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
3809	if (dynamicObject)
3810	dynamicObject->setNumberBeforeTrust(0);
3811	}
3812	numberTest = 0;
3813	}
3814	if (!choiceObject) {
3815	delete choice.possibleBranch;
3816	}
3817	}
3818	if (model->messageHandler()->logLevel() > 3) {
3819	if (anyAction == -2) {
3820	printf("infeasible\n");
3821	} else if (anyAction == -1) {
3822	printf("%d fixed AND choosing %d iDo %d iChosenWhen %d numberToDo %d\n", numberToFix, bestChoice,
3823	iDo, whichChoice, numberToDo);
3824	} else {
3825	int iObject = whichObject[whichChoice];
3826	OsiObject * object = model->modifiableObject(iObject);
3827	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
3828	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
3829	if (dynamicObject) {
3830	int iColumn = dynamicObject->columnNumber();
3831	printf("choosing %d (column %d) iChosenWhen %d numberToDo %d\n", bestChoice,
3832	iColumn, whichChoice, numberToDo);
3833	}
3834	}
3835	}
3836	if (doneHotStart) {
3837	// Delete the snapshot
3838	solver->unmarkHotStart();
3839	// back to normal
3840	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, NULL) ;
3841	// restore basis
3842	solver->setWarmStart(ws);
3843	}
3844	solver->setIntParam(OsiMaxNumIterationHotStart, saveLimit);
3845	// Unless infeasible we will carry on
3846	// But we could fix anyway
3847	if (numberToFix && !hitMaxTime) {
3848	if (anyAction != -2) {
3849	// apply and take off
3850	bool feasible = true;
3851	// can do quick optimality check
3852	int easy = 2;
3853	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, &easy) ;
3854	model->resolve(NULL, 11, saveSolution, saveLower, saveUpper) ;
3855	#ifdef CHECK_DEBUGGER_PATH
3856	if ((model->specialOptions()&1) != 0 && onOptimalPath) {
3857	const OsiRowCutDebugger *debugger = solver->getRowCutDebugger() ;
3858	if (!debugger) {
3859	printf("Strong branching went off optimal path\n");
3860	abort();
3861	}
3862	}
3863	#endif
3864	double newObjValue = solver->getObjSense()*solver->getObjValue();
3865	objectiveValue_ = CoinMax(objectiveValue_,newObjValue);
3866	solver->setHintParam(OsiDoInBranchAndCut, true, OsiHintDo, NULL) ;
3867	feasible = solver->isProvenOptimal();
3868	if (feasible) {
3869	anyAction = 0;
3870	} else {
3871	anyAction = -2;
3872	finished = true;
3873	}
3874	}
3875	}
3876	// If fixed then round again
3877	// See if candidate still possible
3878	if (branch_) {
3879	const OsiObject * object = model->object(bestChoice);
3880	double infeasibility = object->checkInfeasibility(&usefulInfo);
3881	if (!infeasibility) {
3882	// take out
3883	delete branch_;
3884	branch_ = NULL;
3885	} else {
3886	// get preferred way
3887	int preferredWay;
3888	object->infeasibility(&usefulInfo, preferredWay);
3889	CbcBranchingObject * branchObj =
3890	dynamic_cast <CbcBranchingObject *>(branch_) ;
3891	assert (branchObj);
3892	branchObj->way(preferredWay);
3893	#ifdef CBCNODE_TIGHTEN_BOUNDS
3894	bool fixed = branchObj->tighten(solver);
3895	if (fixed) {
3896	//printf("Variable now fixed!\n");
3897	// take out
3898	delete branch_;
3899	branch_ = NULL;
3900	}
3901	#endif
3902	}
3903	}
3904	if (!branch_ && anyAction != -2 && !hitMaxTime) {
3905	finished = false;
3906	}
3907	delete ws;
3908	}
3909	}
3910	// update number of strong iterations etc
3911	model->incrementStrongInfo(numberStrongDone, numberStrongIterations,
3912	anyAction == -2 ? 0 : numberToFix, anyAction == -2);
3913	if (model->searchStrategy() == -1) {
3914	#ifndef COIN_DEVELOP
3915	if (solver->messageHandler()->logLevel() > 1)
3916	#endif
3917	printf("%d strong, %d iters, %d inf, %d not finished, %d not trusted\n",
3918	numberStrongDone, numberStrongIterations, numberStrongInfeasible, numberUnfinished,
3919	numberNotTrusted);
3920	// decide what to do
3921	int strategy = 1;
3922	if (((numberUnfinished*4 > numberStrongDone &&
3923	numberStrongInfeasible*40 < numberStrongDone) \|\|
3924	numberStrongInfeasible < 0) && model->numberStrong() < 10 && model->numberBeforeTrust() <= 20 && model->numberObjects() > CoinMax(1000, solver->getNumRows())) {
3925	strategy = 2;
3926	#ifdef COIN_DEVELOP
3927	//if (model->logLevel()>1)
3928	printf("going to strategy 2\n");
3929	#endif
3930	// Weaken
3931	model->setNumberStrong(2);
3932	model->setNumberBeforeTrust(1);
3933	model->synchronizeNumberBeforeTrust();
3934	}
3935	if (numberNodes)
3936	strategy = 1; // should only happen after hot start
3937	model->setSearchStrategy(strategy);
3938	} else if (numberStrongDone) {
3939	//printf("%d strongB, %d iters, %d inf, %d not finished, %d not trusted\n",
3940	// numberStrongDone,numberStrongIterations,numberStrongInfeasible,numberUnfinished,
3941	// numberNotTrusted);
3942	}
3943	if (model->searchStrategy() == 1 && numberNodes > 500 && numberNodes < -510) {
3944	#ifndef COIN_DEVELOP
3945	if (solver->messageHandler()->logLevel() > 1)
3946	#endif
3947	printf("after %d nodes - %d strong, %d iters, %d inf, %d not finished, %d not trusted\n",
3948	numberNodes, numberStrongDone, numberStrongIterations, numberStrongInfeasible, numberUnfinished,
3949	numberNotTrusted);
3950	// decide what to do
3951	if (numberUnfinished*10 > numberStrongDone + 1 \|\|
3952	!numberStrongInfeasible) {
3953	COIN_DETAIL_PRINT(printf("going to strategy 2\n"));
3954	// Weaken
3955	model->setNumberStrong(2);
3956	model->setNumberBeforeTrust(1);
3957	model->synchronizeNumberBeforeTrust();
3958	model->setSearchStrategy(2);
3959	}
3960	}
3961	if (numberUnfinished*10 < numberStrongDone &&
3962	model->numberStrongIterations()*20 < model->getIterationCount()&&
3963	!auxiliaryInfo->solutionAddsCuts()) {
3964	//printf("increasing trust\n");
3965	model->synchronizeNumberBeforeTrust(2);
3966	}
3967
3968	// Set guessed solution value
3969	guessedObjectiveValue_ = objectiveValue_ + estimatedDegradation;
3970	int kColumn=-1;
3971	if (branch_) {
3972	CbcObject * obj = (dynamic_cast<CbcBranchingObject *>(branch_))->object();
3973	CbcSimpleInteger * branchObj =
3974	dynamic_cast <CbcSimpleInteger *>(obj) ;
3975	if (branchObj) {
3976	kColumn=branchObj->columnNumber();
3977	}
3978	}
3979	#ifdef COIN_HAS_NTY
3980	if (orbitOption&&kColumn>=0) {
3981	CbcSymmetry * symmetryInfo = model->symmetryInfo();
3982	CbcNodeInfo * infoX = lastNode ? lastNode->nodeInfo() : NULL;
3983	bool worthTrying = false;
3984	if (infoX) {
3985	CbcNodeInfo * info = infoX;
3986	for (int i=0;i<NTY_BAD_DEPTH;i++) {
3987	if (!info->parent()) {
3988	worthTrying = true;
3989	break;
3990	}
3991	info = info->parent();
3992	if (info->symmetryWorked()) {
3993	worthTrying = true;
3994	break;
3995	}
3996	}
3997	} else {
3998	worthTrying=true;
3999	}
4000	if (orbitOption==3&&depth_>5)
4001	worthTrying=false;
4002	if (symmetryInfo && worthTrying) {
4003	if ((orbitOption&1)==1) {
4004	symmetryInfo->ChangeBounds(solver->getColLower(),
4005	solver->getColUpper(),
4006	solver->getNumCols(),false);
4007	symmetryInfo->Compute_Symmetry();
4008	symmetryInfo->fillOrbits();
4009	}
4010	const int * orbits = symmetryInfo->whichOrbit();
4011	if (orbits && orbits[kColumn]>=0) {
4012	int numberUsefulOrbits = symmetryInfo->numberUsefulOrbits();
4013	if (solver->messageHandler()->logLevel() > 1)
4014	printf("Orbital Branching on %d - way %d n %d\n",kColumn,way(),numberUsefulOrbits);
4015	if (numberUsefulOrbits<1000\|\|orbitOption==3) {
4016	delete branch_;
4017	branch_ = new CbcOrbitalBranchingObject(model,kColumn,1,0,NULL);
4018	if (infoX)
4019	infoX->setSymmetryWorked();
4020	}
4021	}
4022	}
4023	}
4024	#endif
4025	if (model->logLevel()>1)
4026	printf ("Node %d depth %d unsatisfied %d sum %g obj %g guess %g branching on %d\n",
4027	model->getNodeCount(),depth_,numberUnsatisfied_,
4028	sumInfeasibilities_,objectiveValue_,guessedObjectiveValue_,
4029	kColumn);
4030	#ifdef DO_ALL_AT_ROOT
4031	if (strongType) {
4032	char general[200];
4033	if (strongType==1)
4034	sprintf(general,"Strong branching on all %d unsatisfied, %d iterations (depth %d)\n",
4035	saveNumberToDo,numberStrongIterations,depth_);
4036	else
4037	sprintf(general,"Strong branching on all %d unfixed variables (%d unsatisfied), %d iterations (depth %d)\n",
4038	saveNumberToDo+saveSatisfiedVariables,saveNumberToDo,numberStrongIterations,depth_);
4039	model->messageHandler()->message(CBC_FPUMP2,model->messages())
4040	<< general << CoinMessageEol ;
4041	}
4042	#endif
4043	#ifdef DEBUG_SOLUTION
4044	if(onOptimalPath&&anyAction==-2) {
4045	printf("Gone off optimal path in CbcNode\n");
4046	assert(!onOptimalPath\|\|anyAction!=-2);
4047	}
4048	#endif
4049	/*
4050	Cleanup, then we're finished
4051	*/
4052	if (!model->branchingMethod())
4053	delete decision;
4054
4055	delete choiceObject;
4056	delete [] sort;
4057	delete [] whichObject;
4058	#ifdef RANGING
4059	delete [] objectMark;
4060	#endif
4061	delete [] saveLower;
4062	delete [] saveUpper;
4063	delete [] upEstimate;
4064	delete [] downEstimate;
4065	# ifdef COIN_HAS_CLP
4066	if (osiclp) {
4067	osiclp->setSpecialOptions(saveClpOptions);
4068	}
4069	# endif
4070	// restore solution
4071	solver->setColSolution(saveSolution);
4072	model->reserveCurrentSolution(saveSolution);
4073	delete [] saveSolution;
4074	model->setStateOfSearch(saveStateOfSearch);
4075	model->setLogLevel(saveLogLevel);
4076	// delete extra regions
4077	if (usefulInfo.usefulRegion_) {
4078	delete [] usefulInfo.usefulRegion_;
4079	delete [] usefulInfo.indexRegion_;
4080	delete [] usefulInfo.pi_;
4081	usefulInfo.usefulRegion_ = NULL;
4082	usefulInfo.indexRegion_ = NULL;
4083	usefulInfo.pi_ = NULL;
4084	}
4085	useShadow = model->moreSpecialOptions() & 7;
4086	if ((useShadow == 5 && model->getSolutionCount()) \|\| useShadow == 6) {
4087	// zap pseudo shadow prices
4088	model->pseudoShadow(-1);
4089	// and switch off
4090	model->setMoreSpecialOptions(model->moreSpecialOptions()&(~1023));
4091	}
4092	return anyAction;
4093	}
4094	// 0 is down, 1 is up
4095	typedef struct {
4096	double initialValue; // initial value
4097	double upLowerBound; // Lower bound when going up
4098	double downUpperBound; // Upper bound when going down
4099	double movement[2]; // cost (and initial away from feasible)
4100	double sumModified[2]; // Sum of integer changes
4101	int modified[2]; // Number integers changed
4102	int numIntInfeas[2]; // without odd ones
4103	int numObjInfeas[2]; // just odd ones
4104	bool finished[2]; // true if solver finished
4105	int numIters[2]; // number of iterations in solver (-1 if never solved)
4106	double * integerSolution; // output if thinks integer solution
4107	# ifdef COIN_HAS_CLP
4108	ClpDualRowSteepest * steepest;
4109	#endif
4110	int columnNumber; // Which column it is
4111	} StrongInfo;
4112	typedef struct {
4113	double integerTolerance;
4114	double * originalSolution;
4115	CoinWarmStart * ws;
4116	double * newObjective;
4117	# ifdef COIN_HAS_CLP
4118	ClpDualRowSteepest * dualRowPivot;
4119	ClpPrimalColumnPivot * primalColumnPivot;
4120	# endif
4121	int * back;
4122	int solveType;
4123	} StrongStaticInfo;
4124	typedef struct {
4125	StrongStaticInfo *staticInfo;
4126	StrongInfo * choice;
4127	OsiSolverInterface * solver;
4128	double * tempSolution;
4129	CoinWarmStart * tempBasis;
4130	int whichChoice;
4131	} StrongBundle;
4132	/* return 1 if possible solution (for solveType 100 if infeasible)
4133	2 set if down was infeasible
4134	4 set if up was infeasible
4135	*/
4136	int solveAnalyze(void * info) {
4137	StrongBundle * bundle = reinterpret_cast<StrongBundle *>(info);
4138	StrongInfo * choice = bundle->choice;
4139	StrongStaticInfo * staticInfo = bundle->staticInfo;
4140	OsiSolverInterface * solver = bundle->solver;
4141	int solveType = staticInfo->solveType;
4142	if (solveType==77) {
4143	return 0;
4144	}
4145	const double * saveSolution = staticInfo->originalSolution;
4146	int iColumn = choice->columnNumber;
4147	const int * back = staticInfo->back;
4148	double newObjectiveValue = 1.0e100;
4149	double integerTolerance = staticInfo->integerTolerance;
4150	double bestSolutionValue=COIN_DBL_MAX;
4151	int returnStatus=0;
4152	// status is 0 finished, 1 infeasible and other
4153	int iStatus;
4154	/*
4155	Try the down direction first. (Specify the initial branching alternative as
4156	down with a call to way(-1). Each subsequent call to branch() performs the
4157	specified branch and advances the branch object state to the next branch
4158	alternative.)
4159	*/
4160	for (int iWay=0;iWay<2;iWay++) {
4161	if (choice->numIters[iWay]==0) {
4162	int numberColumns=solver->getNumCols();
4163	if (solveType!=100) {
4164	double saveBound;
4165	if (iWay==0) {
4166	saveBound = solver->getColUpper()[iColumn];
4167	solver->setColUpper(iColumn,choice->downUpperBound);
4168	} else {
4169	saveBound = solver->getColLower()[iColumn];
4170	solver->setColLower(iColumn,choice->upLowerBound);
4171	}
4172	if ((solveType&2)==0) {
4173	solver->solveFromHotStart() ;
4174	} else {
4175	// restore basis
4176	solver->setWarmStart(staticInfo->ws);
4177	# ifdef COIN_HAS_CLP
4178	if (staticInfo->dualRowPivot) {
4179	OsiClpSolverInterface * osiclp = dynamic_cast<OsiClpSolverInterface *>(solver);
4180	ClpSimplex * simplex = osiclp->getModelPtr();
4181	simplex->setDualRowPivotAlgorithm(*staticInfo->dualRowPivot);
4182	//simplex->dualRowPivot()->saveWeights(simplex,4);
4183	simplex->setWhatsChanged(ALL_SAME_EXCEPT_COLUMN_BOUNDS);
4184	simplex->dual(0,5);
4185	} else {
4186	#endif
4187	solver->resolve();
4188	# ifdef COIN_HAS_CLP
4189	}
4190	#endif
4191	}
4192	if (iWay==0)
4193	solver->setColUpper(iColumn,saveBound);
4194	else
4195	solver->setColLower(iColumn,saveBound);
4196	/*
4197	We now have an estimate of objective degradation that we can use for strong
4198	branching. If we're over the cutoff, the variable is monotone up.
4199	If we actually made it to optimality, check for a solution, and if we have
4200	a good one, call setBestSolution to process it. Note that this may reduce the
4201	cutoff, so we check again to see if we can declare this variable monotone.
4202	*/
4203	if (solver->isProvenOptimal()) {
4204	iStatus = 0; // optimal
4205	} else if (solver->isIterationLimitReached()
4206	&& !solver->isDualObjectiveLimitReached()) {
4207	iStatus = 2; // unknown
4208	} else {
4209	iStatus = 1; // infeasible
4210	}
4211	newObjectiveValue = solver->getObjSense() * solver->getObjValue();
4212	choice->numIters[iWay] = solver->getIterationCount();
4213	// Look at interaction
4214	const double * thisSolution = solver->getColSolution();
4215	int numberModified=0;
4216	double sumModified=0.0;
4217	int numberInfeas=0;
4218	for (int i=0;i<numberColumns;i++) {
4219	if (back[i]>=0) {
4220	double value = thisSolution[i];
4221	if (iColumn!=i) {
4222	double difference = fabs(saveSolution[i]-value);
4223	if (difference>integerTolerance) {
4224	numberModified++;
4225	sumModified += difference;
4226	}
4227	}
4228	if (fabs(value-floor(value+0.5))>integerTolerance)
4229	numberInfeas++;;
4230	}
4231	}
4232	choice->numIntInfeas[iWay]=numberInfeas;
4233	choice->sumModified[iWay] = sumModified;
4234	choice->modified[iWay] = numberModified;
4235	if (!iStatus) {
4236	choice->finished[iWay] = true ;
4237	if (!numberInfeas) {
4238	returnStatus=1;
4239	if (!choice->integerSolution) {
4240	bestSolutionValue=newObjectiveValue;
4241	choice->integerSolution=CoinCopyOfArray(thisSolution,numberColumns);;
4242	} else if (bestSolutionValue>newObjectiveValue) {
4243	memcpy(choice->integerSolution,thisSolution,numberColumns*sizeof(double));
4244	}
4245	}
4246	} else if (iStatus == 1) {
4247	newObjectiveValue = 1.0e100 ;
4248	} else {
4249	// Can't say much as we did not finish
4250	choice->finished[iWay] = false ;
4251	}
4252	choice->movement[iWay] = newObjectiveValue ;
4253	} else {
4254	# ifdef COIN_HAS_CLP
4255	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
4256	ClpSimplex * simplex = osiclp ? osiclp->getModelPtr() : NULL;
4257	#endif
4258	// doing continuous and general integer
4259	solver->setColSolution(staticInfo->originalSolution);
4260	solver->setWarmStart(staticInfo->ws);
4261	double saveBound;
4262	double newBound;
4263	if (iWay==0) {
4264	saveBound=solver->getColUpper()[iColumn];
4265	solver->setColUpper(iColumn,choice->downUpperBound);
4266	newBound=choice->downUpperBound;
4267	} else {
4268	saveBound=solver->getColLower()[iColumn];
4269	solver->setColLower(iColumn,choice->upLowerBound);
4270	newBound=choice->upLowerBound;
4271	}
4272	# if 0 //def COIN_HAS_CLP
4273	if (simplex) {
4274	// set solution to new bound (if basic will be recomputed)
4275	simplex->primalColumnSolution()[iColumn]=newBound;
4276	}
4277	#endif
4278	solver->setHintParam(OsiDoDualInResolve, true, OsiHintDo) ;
4279	#define PRINT_ANALYZE 0
4280	#if PRINT_ANALYZE>0
4281	osiclp->getModelPtr()->setLogLevel(1);
4282	solver->setHintParam(OsiDoReducePrint, false, OsiHintTry);
4283	#endif
4284	solver->resolve();
4285	if (iWay==0) {
4286	#if PRINT_ANALYZE>0
4287	printf("column %d down original %g <= %g <= %g upper now %g - result %s\n",
4288	iColumn,solver->getColLower()[iColumn],
4289	staticInfo->originalSolution[iColumn],saveBound,
4290	newBound,solver->isProvenOptimal() ? "ok" : "infeas");
4291	#endif
4292	solver->setColUpper(iColumn,saveBound);
4293	} else {
4294	#if PRINT_ANALYZE>0
4295	printf("column %d up original %g <= %g <= %g lower now %g - result %s\n",
4296	iColumn,saveBound,staticInfo->originalSolution[iColumn],
4297	solver->getColUpper()[iColumn],
4298	newBound,solver->isProvenOptimal() ? "ok" : "infeas");
4299	#endif
4300	solver->setColLower(iColumn,saveBound);
4301	}
4302	choice->numIters[iWay] = solver->getIterationCount();
4303	if (solver->isProvenOptimal()) {
4304	//printf("Way %d - all way %d iterations - column %d\n",
4305	// iWay,solver->getIterationCount(),iColumn);
4306	// can go all way
4307	choice->movement[iWay] = newBound;
4308	} else {
4309	// zero objective
4310	double offset;
4311	solver->getDblParam(OsiObjOffset,offset);
4312	solver->setDblParam(OsiObjOffset, 0.0);
4313	solver->setObjective(staticInfo->newObjective+numberColumns);
4314	if (iWay==0) {
4315	solver->setObjCoeff(iColumn,1.0);
4316	} else {
4317	solver->setObjCoeff(iColumn,-1.0);
4318	}
4319	solver->setColSolution(staticInfo->originalSolution);
4320	solver->setWarmStart(staticInfo->ws);
4321	solver->setHintParam(OsiDoDualInResolve, false, OsiHintDo) ;
4322	solver->resolve();
4323	//printf("Way %d - first solve %d iterations, second %d - column %d\n",
4324	// iWay,choice->numIters[iWay],solver->getIterationCount(),iColumn);
4325	choice->movement[iWay] = solver->getColSolution()[iColumn];
4326	choice->numIters[iWay] += solver->getIterationCount();
4327	#if PRINT_ANALYZE>0
4328	if (iWay==0) {
4329	printf("column %d down can get to %g - result %s\n",
4330	iColumn,solver->getColSolution()[iColumn],solver->isProvenOptimal() ? "ok" : "infeas");
4331	} else {
4332	printf("column %d up can get to %g - result %s\n",
4333	iColumn,solver->getColSolution()[iColumn],solver->isProvenOptimal() ? "ok" : "infeas");
4334	}
4335	#endif
4336	// reset objective
4337	solver->setDblParam(OsiObjOffset, offset);
4338	solver->setObjective(staticInfo->newObjective);
4339	if (!solver->isProvenOptimal()) {
4340	# ifdef COIN_HAS_CLP
4341	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
4342	ClpSimplex * simplex = osiclp->getModelPtr();
4343	double sum = simplex->sumPrimalInfeasibilities();
4344	sum /= static_cast<double>(simplex->numberPrimalInfeasibilities());
4345	if (sum>1.0e-3) {
4346	#endif
4347	choice->modified[0]=1;
4348	returnStatus=1;
4349	solver->writeMps("bad","mps");
4350	abort();
4351	# ifdef COIN_HAS_CLP
4352	}
4353	#endif
4354	}
4355	}
4356	//solver->setObjCoeff(iColumn,0.0);
4357	}
4358	}
4359	}
4360	return returnStatus;
4361	}
4362	#ifdef THREADS_IN_ANALYZE
4363	void * cbc_parallelManager(void * stuff)
4364	{
4365	CoinPthreadStuff * driver = reinterpret_cast<CoinPthreadStuff *>(stuff);
4366	int whichThread=driver->whichThread();
4367	CoinThreadInfo * threadInfo = driver->threadInfoPointer(whichThread);
4368	threadInfo->status=-1;
4369	int * which = threadInfo->stuff;
4370	pthread_barrier_wait(driver->barrierPointer());
4371	#if 0
4372	int status=-1;
4373	while (status!=100)
4374	status=timedWait(driver,1000,2);
4375	pthread_cond_signal(driver->conditionPointer(1));
4376	pthread_mutex_unlock(driver->mutexPointer(1,whichThread));
4377	#endif
4378	// so now mutex_ is locked
4379	int whichLocked=0;
4380	while (true) {
4381	pthread_mutex_t * mutexPointer = driver->mutexPointer(whichLocked,whichThread);
4382	// wait
4383	//printf("Child waiting for %d - status %d %d %d\n",
4384	// whichLocked,lockedX[0],lockedX[1],lockedX[2]);
4385	#ifdef DETAIL_THREAD
4386	printf("thread %d about to lock mutex %d\n",whichThread,whichLocked);
4387	#endif
4388	pthread_mutex_lock (mutexPointer);
4389	whichLocked++;
4390	if (whichLocked==3)
4391	whichLocked=0;
4392	int unLock=whichLocked+1;
4393	if (unLock==3)
4394	unLock=0;
4395	//printf("child pointer %p status %d\n",threadInfo,threadInfo->status);
4396	assert(threadInfo->status>=0);
4397	if (threadInfo->status==1000)
4398	pthread_exit(NULL);
4399	int type=threadInfo->status;
4400	int & returnCode=which[0];
4401	int iPass=which[1];
4402	//CoinIndexedVector * array;
4403	//double dummy;
4404	switch(type) {
4405	// dummy
4406	case 0:
4407	break;
4408	case 1:
4409	returnCode=solveAnalyze(threadInfo->extraInfo);
4410	threadInfo->stuff[3]=0;
4411	break;
4412	case 100:
4413	// initialization
4414	break;
4415	}
4416	threadInfo->status= (type!=1) ? -1 : -2;
4417	#ifdef DETAIL_THREAD
4418	printf("thread %d about to unlock mutex %d\n",whichThread,unLock);
4419	#endif
4420	pthread_mutex_unlock (driver->mutexPointer(unLock,whichThread));
4421	}
4422	}
4423	#endif
4424	int CbcNode::analyze (CbcModel model, double results)
4425	{
4426	#define COIN_DETAIL
4427	int i;
4428	int numberIterationsAllowed = model->numberAnalyzeIterations();
4429	int numberColumns = model->getNumCols();
4430	int numberRows = model->getNumRows();
4431	int numberObjects = model->numberObjects();
4432	int numberIntegers = model->numberIntegers();
4433	int numberLookIntegers=0;
4434	int highestPriority=COIN_INT_MAX;
4435	int * back = new int[numberColumns];
4436	const int * integerVariable = model->integerVariable();
4437	for (i = 0; i < numberIntegers; i++) {
4438	highestPriority = CoinMin(highestPriority,model->modifiableObject(i)->priority());
4439	}
4440	for (i = 0; i < numberColumns; i++)
4441	back[i] = -1;
4442	for (i = 0; i < numberIntegers; i++) {
4443	int iColumn = integerVariable[i];
4444	back[iColumn] = i;
4445	if (model->modifiableObject(i)->priority()==highestPriority) {
4446	numberLookIntegers++;
4447	} else {
4448	back[iColumn] = i+numberColumns;
4449	}
4450	}
4451	/*
4452	0 - just look
4453	0 (1) bit - use to set priorities
4454	1 (2) bit - look at bounds on all variables and more iterations
4455	2 (4) bit - do threaded (if parallelMode()==1 then not repeatable if any fixed)
4456	3 (8) bit -
4457	4 (16) bit - do even if m*n>1,000,000
4458	5 (32) bit - printing time
4459	6 (64) bit - save mps file
4460	*/
4461	int solveType;
4462	char general[200];
4463	if (numberIterationsAllowed>0) {
4464	solveType = 0;
4465	} else {
4466	solveType = - numberIterationsAllowed;
4467	if ((solveType&16)==0) {
4468	double size=numberRows;
4469	size*=numberLookIntegers;
4470	if (size>1000000) {
4471	if ((solveType&32)!=0)
4472	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4473	<< "Skipping analyze as problem too large"
4474	<< CoinMessageEol;
4475	return 0;
4476	}
4477	}
4478	sprintf(general,"Analyze options %d",solveType);
4479	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4480	<< general
4481	<< CoinMessageEol;
4482	if ((solveType&1)!=0)
4483	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4484	<< "Using to set priorities (probably bad idea)"
4485	<< CoinMessageEol;
4486	if ((solveType&2)!=0)
4487	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4488	<< "Use more iterations and look at continuous/general integer variables"
4489	<< CoinMessageEol;
4490	if ((solveType&4)!=0)
4491	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4492	<< "Use threads"
4493	<< CoinMessageEol;
4494	if ((solveType&32)!=0)
4495	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4496	<< "32 switches on more printing, (16 bit allows large problems)"
4497	<< CoinMessageEol;
4498	}
4499	OsiSolverInterface * solver = model->solver();
4500	objectiveValue_ = solver->getObjSense() * solver->getObjValue();
4501	const double * lower = solver->getColLower();
4502	const double * upper = solver->getColUpper();
4503	const double * dj = solver->getReducedCost();
4504	// What results is
4505	double * newLower = results;
4506	double * objLower = newLower + numberIntegers;
4507	double * newUpper = objLower + numberIntegers;
4508	double * objUpper = newUpper + numberIntegers;
4509	double * interAction = objUpper + numberIntegers;
4510	for (i = 0; i < numberIntegers; i++) {
4511	int iColumn = integerVariable[i];
4512	newLower[i] = lower[iColumn];
4513	objLower[i] = -COIN_DBL_MAX;
4514	newUpper[i] = upper[iColumn];
4515	objUpper[i] = -COIN_DBL_MAX;
4516	interAction[i] = 0.0;
4517	}
4518	double * objMovement=new double[2*numberIntegers];
4519	memset(objMovement,0,2numberIntegerssizeof(double));
4520	double * saveUpper = new double[numberColumns];
4521	double * saveLower = new double[numberColumns];
4522	// Save solution in case heuristics need good solution later
4523
4524	double * saveSolution = new double[numberColumns];
4525	memcpy(saveSolution, solver->getColSolution(), numberColumns*sizeof(double));
4526	model->reserveCurrentSolution(saveSolution);
4527	for (i = 0; i < numberColumns; i++) {
4528	saveLower[i] = lower[i];
4529	saveUpper[i] = upper[i];
4530	}
4531	// Get arrays to sort
4532	double * sort = new double[numberObjects];
4533	int * whichObject = new int[numberObjects];
4534	int numberToFix = 0;
4535	int numberToDo = 0;
4536	double integerTolerance =
4537	model->getDblParam(CbcModel::CbcIntegerTolerance);
4538	// point to useful information
4539	OsiBranchingInformation usefulInfo = model->usefulInformation();
4540	// and modify
4541	usefulInfo.depth_ = depth_;
4542
4543	// compute current state
4544	int numberObjectInfeasibilities; // just odd ones
4545	int numberIntegerInfeasibilities;
4546	model->feasibleSolution(
4547	numberIntegerInfeasibilities,
4548	numberObjectInfeasibilities);
4549	if (solveType) {
4550	if ((solveType&2)==0)
4551	numberIterationsAllowed=200*numberIntegerInfeasibilities;
4552	else
4553	numberIterationsAllowed=COIN_INT_MAX;
4554	}
4555	int saveAllowed=numberIterationsAllowed;
4556	# ifdef COIN_HAS_CLP
4557	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
4558	int saveClpOptions = 0;
4559	bool fastIterations = (model->specialOptions() & 8) != 0;
4560	if (osiclp) {
4561	saveClpOptions = osiclp->specialOptions();
4562	// for faster hot start
4563	if (fastIterations)
4564	osiclp->setSpecialOptions(saveClpOptions \| 8192);
4565	else
4566	osiclp->setSpecialOptions(saveClpOptions \| 2048); // switch off crunch
4567	}
4568	# else
4569	bool fastIterations = false ;
4570	# endif
4571	/*
4572	Scan for branching objects that indicate infeasibility.
4573
4574	The algorithm is to fill the array with a set of good candidates (by
4575	infeasibility).
4576
4577	*/
4578	numberToDo = 0;
4579	for (i = 0; i < numberObjects; i++) {
4580	OsiObject * object = model->modifiableObject(i);
4581	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
4582	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
4583	if (!dynamicObject)
4584	continue;
4585	if (dynamicObject->priority()!=highestPriority)
4586	continue;
4587	double infeasibility = object->checkInfeasibility(&usefulInfo);
4588	int iColumn = dynamicObject->columnNumber();
4589	if (saveUpper[iColumn] == saveLower[iColumn])
4590	continue;
4591	if (infeasibility)
4592	sort[numberToDo] = -1.0e10 - infeasibility;
4593	else
4594	sort[numberToDo] = -fabs(dj[iColumn]);
4595	whichObject[numberToDo++] = i;
4596	}
4597	// Save basis
4598	CoinWarmStart * ws = solver->getWarmStart();
4599	int saveLimit;
4600	solver->getIntParam(OsiMaxNumIterationHotStart, saveLimit);
4601	int targetIterations = CoinMax(500, numberIterationsAllowed / numberObjects);
4602	if (saveLimit < targetIterations)
4603	solver->setIntParam(OsiMaxNumIterationHotStart, targetIterations);
4604	if ((solveType&2)==0) {
4605	// Mark hot start
4606	solver->markHotStart();
4607	}
4608	solver->setHintParam(OsiDoDualInResolve, true, OsiHintDo) ;
4609	// Sort
4610	CoinSort_2(sort, sort + numberToDo, whichObject);
4611	double * currentSolution = model->currentSolution();
4612	double objMin = 1.0e50;
4613	double objMax = -1.0e50;
4614	bool needResolve = false;
4615	int maxChoices=1;
4616	int currentChoice=0;
4617	int numberThreads=0;
4618	bool doAtEnd=false;
4619	if (model->parallelMode() && (solveType&4)!=0) {
4620	numberThreads=model->getNumberThreads();
4621	sprintf(general,"Using %d threads in analysis\n",numberThreads);
4622	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4623	<< general
4624	<< CoinMessageEol;
4625	if (model->parallelMode()==1) {
4626	maxChoices=numberThreads;
4627	} else {
4628	maxChoices = numberToDo;
4629	if ((solveType&2)!=0)
4630	maxChoices = numberColumns;
4631	doAtEnd=true;
4632	}
4633	}
4634	StrongInfo * choices = new StrongInfo[maxChoices];
4635	StrongStaticInfo staticInfo;
4636	int numberBundles = CoinMax(1,numberThreads);
4637	StrongBundle * bundles = new StrongBundle[numberBundles];
4638	/*
4639	0 - available - no need to look at results
4640	1 - not available
4641	2 - available - need to look at results
4642	*/
4643	#ifndef NUMBER_THREADS
4644	#define NUMBER_THREADS 4
4645	#endif
4646	int status[NUMBER_THREADS];
4647	memset(status,0,sizeof(status));
4648	memset(&staticInfo,0,sizeof(staticInfo));
4649	staticInfo.solveType = solveType;
4650	staticInfo.originalSolution=saveSolution;
4651	staticInfo.back=back;
4652	staticInfo.ws=ws;
4653	staticInfo.integerTolerance=integerTolerance;
4654	double time1 = model->getCurrentSeconds();
4655	#define DO_STEEPEST_SERIAL 1
4656	# ifdef COIN_HAS_CLP
4657	if (osiclp&&(solveType&2)!=0&&(!numberThreads\|\|DO_STEEPEST_SERIAL)) {
4658	ClpSimplex * simplex = osiclp->getModelPtr();
4659	simplex->setLogLevel(0);
4660	simplex->dual(0,1);
4661	ClpDualRowPivot * dualRowPivot=simplex->dualRowPivot();
4662	ClpDualRowSteepest * steep = dynamic_cast<ClpDualRowSteepest *>(dualRowPivot);
4663	if (steep) {
4664	staticInfo.dualRowPivot=new ClpDualRowSteepest (*steep);
4665	staticInfo.dualRowPivot->setMode(1); // full steepest edge
4666	simplex->spareIntArray_[0]=0;
4667	simplex->spareIntArray_[1]=numberRows;
4668	staticInfo.dualRowPivot->saveWeights(simplex,7);
4669	}
4670	}
4671	#endif
4672	for (int i=0;i<numberBundles;i++) {
4673	memset(bundles+i,0,sizeof(StrongBundle));
4674	bundles[i].staticInfo=&staticInfo;
4675	}
4676	#if defined (THREADS_IN_ANALYZE) && defined (COIN_HAS_CLP)
4677	#define USE_STRONG_THREADS
4678	CoinPthreadStuff threadInfo(numberThreads,cbc_parallelManager);
4679	int threadNeedsRefreshing[NUMBER_THREADS];
4680	for (int i=0;i<numberThreads;i++) {
4681	threadInfo.threadInfo_[i].extraInfo2 = solver->clone();
4682	threadNeedsRefreshing[i]=0;
4683	}
4684	# ifdef COIN_HAS_CLP
4685	int numberSteepThreads=0;
4686	int step=numberThreads ? (numberRows+numberThreads-1)/numberThreads : 0;
4687	int first=0;
4688	for (int i=0;i<numberThreads;i++) {
4689	if (osiclp&&(solveType&2)!=0&&!DO_STEEPEST_SERIAL) {
4690	OsiSolverInterface * solver=
4691	reinterpret_cast<OsiSolverInterface *>(threadInfo.threadInfo_[i].extraInfo2);
4692	OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver);
4693	ClpSimplex * simplex = osiclp->getModelPtr();
4694	simplex->setLogLevel(0);
4695	simplex->dual(0,1);
4696	ClpDualRowPivot * dualRowPivot=simplex->dualRowPivot();
4697	ClpDualRowSteepest * steep = dynamic_cast<ClpDualRowSteepest *>(dualRowPivot);
4698	if (steep) {
4699	numberSteepThreads=numberThreads;
4700	ClpDualRowSteepest * dualRowPivot=new ClpDualRowSteepest (*steep);
4701	dualRowPivot->setMode(1); // full steepest edge
4702	simplex->spareIntArray_[0]=0;
4703	simplex->spareIntArray_[1]=numberRows;
4704	simplex->spareIntArray_[0]=first;
4705	simplex->spareIntArray_[1]=CoinMin(first+step,numberRows);
4706	first += step;
4707	if (i==0)
4708	staticInfo.dualRowPivot=dualRowPivot;
4709	choices[i].steepest=dualRowPivot;
4710	dualRowPivot->saveWeights(simplex,7);
4711	}
4712	}
4713	}
4714	if (numberSteepThreads&&false) {
4715	int numberDone=0;
4716	int iDo=0;
4717	staticInfo.solveType = 200;
4718	while (numberDone<numberSteepThreads) {
4719	int iThread;
4720	threadInfo.waitParallelTask(1,iThread,iDo<numberToDo);
4721	int threadStatus = 1+threadInfo.threadInfo_[iThread].status;
4722	iThread=iThread;
4723	if (threadStatus==0&&iDo<numberSteepThreads) {
4724	StrongInfo & choice = choices[iThread];
4725	StrongBundle & bundle = bundles[iThread];
4726	bundle.whichChoice=iThread;
4727	memset(&choice,0,sizeof(StrongInfo));
4728	iDo++; //started this one
4729	bundle.choice=&choice;
4730	bundle.solver = solver;
4731	bundle.solver=reinterpret_cast<OsiSolverInterface *>(threadInfo.threadInfo_[iThread].extraInfo2);
4732	threadStatus=0;
4733	#ifdef DETAIL_THREAD
4734	printf("Starting steep task on thread %d\n",
4735	choice.iThread);
4736	#endif
4737	threadInfo.startParallelTask(1,iThread,&bundle);
4738	}
4739	if (!threadStatus) {
4740	#ifdef _MSC_VER
4741	Sleep(1);
4742	#else
4743	usleep(1000);
4744	#endif
4745	continue;
4746	}
4747	if (threadStatus) {
4748	numberDone++;
4749	// say available
4750	threadInfo.sayIdle(iThread);
4751	}
4752	staticInfo.solveType = solveType;
4753	}
4754	OsiSolverInterface * solver0=
4755	reinterpret_cast<OsiSolverInterface *>(threadInfo.threadInfo_[0].extraInfo2);
4756	CoinIndexedVector * savedWeights0 = staticInfo.dualRowPivot->savedWeights();
4757	int * index0 = savedWeights0->getIndices();
4758	double * weight0 = savedWeights0->denseVector();
4759	int step=(numberRows+numberSteepThreads-1)/numberSteepThreads;
4760	int first=step;
4761	//memset(weight0+first,0,(numberRows-first)*sizeof(double));
4762	for (int i=1;i<numberSteepThreads;i++) {
4763	int n=CoinMin(step,numberRows-first);
4764	CoinIndexedVector * savedWeights = choices[i].steepest->savedWeights();
4765	int * index = savedWeights->getIndices();
4766	double * weight = savedWeights->denseVector();
4767	memcpy(index0+first,index+first,n*sizeof(int));
4768	memcpy(weight0+first,weight+first,n*sizeof(double));
4769	first += step;
4770	delete choices[i].steepest;
4771	choices[i].steepest=NULL;
4772	}
4773	//for (int j=0;j<numberRows;j++)
4774	//weight0[j]=1.0;
4775	}
4776	#endif
4777	#endif
4778	double bestSolutionValue = model->getMinimizationObjValue();
4779	double * bestSolution = NULL;
4780	double cutoff;
4781	solver->getDblParam(OsiDualObjectiveLimit,cutoff);
4782	double maxMovement = 2.0*(cutoff-objectiveValue_)+1.0e-6;
4783	/*
4784	Now calculate the cost forcing the variable up and down.
4785	*/
4786	int iDo=0;
4787	int iDone=-1;
4788	int numberDone=0;
4789	int iThread=0;
4790	int threadStatus=0;
4791	int whenPrint = (numberToDo+9)/10;
4792	while (numberDone<numberToDo) {
4793	if ((solveType&32)!=0&&numberDone==whenPrint) {
4794	whenPrint += (numberToDo+9)/10;
4795	sprintf(general,"%d variables looked at - %d changed by initial strong branching (%.2f seconds - %d iterations)",numberDone,numberToFix,model->getCurrentSeconds()-time1,saveAllowed-numberIterationsAllowed);
4796	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
4797	<< general
4798	<< CoinMessageEol;
4799	}
4800	#ifdef USE_STRONG_THREADS
4801	if (numberThreads) {
4802	threadInfo.waitParallelTask(1,iThread,iDo<numberToDo);
4803	threadStatus = 1+threadInfo.threadInfo_[iThread].status;
4804	if (!doAtEnd)
4805	currentChoice=iThread;
4806	if (threadNeedsRefreshing[iThread]) {
4807	OsiSolverInterface * solver=
4808	reinterpret_cast<OsiSolverInterface *>(threadInfo.threadInfo_[iThread].extraInfo2);
4809	if ((threadNeedsRefreshing[iThread]&1)!=0)
4810	solver->setColLower(saveLower);
4811	if ((threadNeedsRefreshing[iThread]&2)!=0)
4812	solver->setColUpper(saveUpper);
4813	threadNeedsRefreshing[iThread]=0;
4814	}
4815	}
4816	#endif
4817	if (threadStatus==0&&iDo<numberToDo) {
4818	StrongInfo & choice = choices[currentChoice];
4819	StrongBundle & bundle = bundles[iThread];
4820	bundle.whichChoice=currentChoice;
4821	memset(&choice,0,sizeof(StrongInfo));
4822	int iObject = whichObject[iDo];
4823	iDo++; //started this one
4824	OsiObject * object = model->modifiableObject(iObject);
4825	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
4826	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
4827	int iColumn = dynamicObject->columnNumber();
4828	double value = currentSolution[iColumn];
4829	double nearest = floor(value + 0.5);
4830	double lowerValue = floor(value);
4831	bool satisfied = false;
4832	if (fabs(value - nearest) <= integerTolerance \|\|
4833	value < saveLower[iColumn] \|\| value > saveUpper[iColumn]) {
4834	satisfied = true;
4835	if (nearest < saveUpper[iColumn]) {
4836	lowerValue = nearest;
4837	} else {
4838	lowerValue = nearest - 1;
4839	}
4840	}
4841	double upperValue = lowerValue + 1.0;
4842	// Save which object it was
4843	choice.columnNumber = iColumn;
4844	choice.initialValue=value;
4845	choice.upLowerBound=upperValue;
4846	choice.downUpperBound=lowerValue;
4847	choice.numIntInfeas[1] = numberUnsatisfied_;
4848	choice.numIntInfeas[0] = numberUnsatisfied_;
4849	choice.movement[0] = 0.0;
4850	choice.movement[1] = 0.0;
4851	choice.numIters[0] = 0;
4852	choice.numIters[1] = 0;
4853	if (fabs(value - lowerValue) <= integerTolerance)
4854	choice.numIters[0]=-1; // mark as not done
4855	if (fabs(value - upperValue) <= integerTolerance)
4856	choice.numIters[1]=-1; // mark as not done
4857	bundle.choice=&choice;
4858	bundle.solver = solver;
4859	#ifdef USE_STRONG_THREADS
4860	if (numberThreads) {
4861	bundle.solver=reinterpret_cast<OsiSolverInterface *>(threadInfo.threadInfo_[iThread].extraInfo2);
4862	threadStatus=0;
4863	#ifdef DETAIL_THREAD
4864	printf("Starting task for column %d on thread %d\n",
4865	choice.columnNumber,iThread);
4866	#endif
4867	threadInfo.startParallelTask(1,iThread,&bundle);
4868	} else {
4869	#endif
4870	threadStatus=2;
4871	solveAnalyze(&bundle);
4872	#ifdef USE_STRONG_THREADS
4873	}
4874	#endif
4875	}
4876	if (!threadStatus) {
4877	#ifdef _MSC_VER
4878	Sleep(1);
4879	#else
4880	usleep(1000);
4881	#endif
4882	continue;
4883	}
4884	if (threadStatus) {
4885	int whichChoice = bundles[iThread].whichChoice;
4886	StrongInfo & choice = choices[whichChoice];
4887	int iColumn=choice.columnNumber;
4888	if (choice.integerSolution) {
4889	double * foundSolution = choice.integerSolution;
4890	solver->setColSolution(foundSolution);
4891	// See if integer solution
4892	int numberInfeas=0;
4893	int numberOddInfeas=0;
4894	if (model->feasibleSolution(numberInfeas,numberOddInfeas)
4895	&& model->problemFeasibility()->feasible(model, -1) >= 0) {
4896	double newObjectiveValue;
4897	solver->getDblParam(OsiObjOffset,newObjectiveValue);
4898	newObjectiveValue=-newObjectiveValue;
4899	const double * cost = solver->getObjCoefficients();
4900	for ( int i = 0 ; i < numberColumns ; i++ )
4901	newObjectiveValue += cost[i] * foundSolution[i];
4902	if (newObjectiveValue<bestSolutionValue) {
4903	if (doAtEnd) {
4904	if (!bestSolution)
4905	bestSolution = CoinCopyOfArray(foundSolution,numberColumns);
4906	else
4907	memcpy(bestSolution,foundSolution,numberColumns*sizeof(double));
4908	bestSolutionValue=newObjectiveValue;
4909	} else {
4910	model->setBestSolution(CBC_STRONGSOL,
4911	newObjectiveValue,
4912	foundSolution) ;
4913	model->setLastHeuristic(NULL);
4914	model->incrementUsed(solver->getColSolution());
4915	bestSolutionValue = model->getMinimizationObjValue();
4916	}
4917	}
4918	}
4919	delete [] foundSolution;
4920	}
4921	for (int iWay=0;iWay<2;iWay++) {
4922	numberIterationsAllowed -= choice.numIters[iWay];
4923	choice.movement[iWay] -= objectiveValue_;
4924	}
4925	// If objective goes above certain amount we can set bound
4926	int jInt = back[iColumn];
4927	OsiObject * object = model->modifiableObject(jInt);
4928	CbcSimpleIntegerDynamicPseudoCost * dynamicObject =
4929	dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ;
4930	if (dynamicObject) {
4931	if (choice.numIters[0]>=0) {
4932	dynamicObject->addToSumDownCost(CoinMin(choice.movement[0],maxMovement));
4933	dynamicObject->addToSumDownChange(choice.initialValue-choice.downUpperBound);
4934	}
4935	if (choice.numIters[1]>=0) {
4936	dynamicObject->addToSumUpCost(CoinMin(choice.movement[1],maxMovement));
4937	dynamicObject->addToSumUpChange(choice.upLowerBound-choice.initialValue);
4938	}
4939	}
4940	newLower[jInt] = choice.upLowerBound;
4941	if (choice.finished[0])
4942	objLower[jInt] = choice.movement[0] + objectiveValue_;
4943	else
4944	objLower[jInt] = objectiveValue_;
4945	newUpper[jInt] = choice.downUpperBound;
4946	if (choice.finished[1])
4947	objUpper[jInt] = choice.movement[1] + objectiveValue_;
4948	else
4949	objUpper[jInt] = objectiveValue_;
4950	objMin = CoinMin(CoinMin(objLower[jInt], objUpper[jInt]), objMin);
4951	objMovement[2*jInt]=choice.movement[0];
4952	objMovement[2*jInt+1]=choice.movement[1];
4953	double sumModified = choice.modified[0] + choice.modified[1] +
4954	1.0e-15*(choice.sumModified[0]+choice.sumModified[1]);
4955	if (choice.numIters[0]>=0&&choice.numIters[1]>=0)
4956	sumModified *= 0.6;
4957	interAction[jInt] = sumModified;
4958	/*
4959	End of evaluation for this candidate variable. Possibilities are:
4960	* Both sides below cutoff; this variable is a candidate for branching.
4961	* Both sides infeasible or above the objective cutoff: no further action
4962	here. Break from the evaluation loop and assume the node will be purged
4963	by the caller.
4964	* One side below cutoff: Install the branch (i.e., fix the variable). Break
4965	from the evaluation loop and assume the node will be reoptimised by the
4966	caller.
4967	*/
4968	threadStatus=0;
4969	currentChoice++;
4970	numberDone++;
4971	#ifdef USE_STRONG_THREADS
4972	// say available
4973	if (numberThreads) {
4974	threadInfo.sayIdle(iThread);
4975	}
4976	#endif
4977	if (doAtEnd)
4978	continue;
4979	if (choice.movement[1] < 1.0e100) {
4980	if (choice.movement[0] < 1.0e100) {
4981	objMax = CoinMax(CoinMax(objLower[jInt], objUpper[jInt]), objMax);
4982	// In case solution coming in was odd
4983	choice.movement[1] = CoinMax(0.0, choice.movement[1]);
4984	choice.movement[0] = CoinMax(0.0, choice.movement[0]);
4985	// feasible -
4986	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
4987	<< iColumn << iColumn
4988	<< choice.movement[0] << choice.numIntInfeas[0]
4989	<< choice.movement[1] << choice.numIntInfeas[1]
4990	<< choice.initialValue
4991	<< CoinMessageEol;
4992	} else {
4993	// up feasible, down infeasible
4994	needResolve = true;
4995	numberToFix++;
4996	saveLower[iColumn] = choice.upLowerBound;
4997	solver->setColLower(iColumn, choice.upLowerBound);
4998	#ifdef USE_STRONG_THREADS
4999	for (int i=0;i<numberThreads;i++) {
5000	threadNeedsRefreshing[i] \|= 1;
5001	}
5002	#endif
5003	}
5004	} else {
5005	if (choice.movement[0] < 1.0e100) {
5006	// down feasible, up infeasible
5007	needResolve = true;
5008	numberToFix++;
5009	saveUpper[iColumn] = choice.downUpperBound;
5010	solver->setColUpper(iColumn, choice.downUpperBound);
5011	#ifdef USE_STRONG_THREADS
5012	for (int i=0;i<numberThreads;i++) {
5013	threadNeedsRefreshing[i] \|= 2;
5014	}
5015	#endif
5016	} else {
5017	// neither side feasible
5018	COIN_DETAIL_PRINT(printf("Both infeasible for choice %d sequence %d\n", i,
5019	model->object(choice.objectNumber)->columnNumber()));
5020	//solver->writeMps("bad");
5021	numberToFix = -1;
5022	break;
5023	}
5024	}
5025	if (numberIterationsAllowed <= 0)
5026	break;
5027	if (currentChoice==maxChoices)
5028	currentChoice=0;
5029	}
5030	//printf("obj %d, col %d, down %g up %g value %g\n",iObject,iColumn,
5031	// choice.downMovement,choice.upMovement,value);
5032	}
5033	// Do at end if deterministic
5034	if (doAtEnd) {
5035	if (bestSolution) {
5036	model->setBestSolution(CBC_STRONGSOL,
5037	bestSolutionValue,
5038	bestSolution) ;
5039	model->setLastHeuristic(NULL);
5040	model->incrementUsed(solver->getColSolution());
5041	delete [] bestSolution;
5042	}
5043	for (int iDo = 0; iDo < numberLookIntegers; iDo++) {
5044	StrongInfo & choice = choices[iDo];
5045	int iColumn = choice.columnNumber;
5046	int iObject = iColumn;
5047	int jInt = back[iColumn];
5048	double value = choice.initialValue;
5049	double lowerValue = choice.downUpperBound;
5050	double upperValue = choice.upLowerBound;
5051	if (choice.movement[1] < 1.0e100) {
5052	if (choice.movement[0] < 1.0e100) {
5053	objMax = CoinMax(CoinMax(objLower[jInt], objUpper[jInt]), objMax);
5054	// In case solution coming in was odd
5055	choice.movement[1] = CoinMax(0.0, choice.movement[1]);
5056	choice.movement[0] = CoinMax(0.0, choice.movement[0]);
5057	// feasible -
5058	model->messageHandler()->message(CBC_STRONG, *model->messagesPointer())
5059	<< iObject << iColumn
5060	<< choice.movement[0] << choice.numIntInfeas[0]
5061	<< choice.movement[1] << choice.numIntInfeas[1]
5062	<< value
5063	<< CoinMessageEol;
5064	} else {
5065	// up feasible, down infeasible
5066	numberToFix++;
5067	saveLower[iColumn] = upperValue;
5068	solver->setColLower(iColumn, upperValue);
5069	}
5070	} else {
5071	if (choice.movement[0] < 1.0e100) {
5072	// down feasible, up infeasible
5073	needResolve = true;
5074	numberToFix++;
5075	saveUpper[iColumn] = lowerValue;
5076	solver->setColUpper(iColumn, lowerValue);
5077	} else {
5078	// neither side feasible
5079	COIN_DETAIL_PRINT(printf("Both infeasible for choice %d sequence %d\n", i,
5080	model->object(choice.objectNumber)->columnNumber()));
5081	//solver->writeMps("bad");
5082	numberToFix = -1;
5083	break;
5084	}
5085	}
5086	}
5087	}
5088	if (false) {
5089	const double * lower = solver->getColLower();
5090	const double * upper = solver->getColUpper();
5091	for (int i=0;i<numberColumns;i++) {
5092	if (lower[i]!=saveLower[i]\|\|upper[i]!=saveUpper[i]) {
5093	printf("%d changed- saved %g,%g now %g,%g\n",i,saveLower[i],saveUpper[i],
5094	lower[i],upper[i]);
5095	}
5096	}
5097	}
5098	COIN_DETAIL_PRINT(printf("Best possible solution %g, can fix more if solution of %g found - looked at %d variables in %d iterations\n",
5099	objMin, objMax, iDo, model->numberAnalyzeIterations() - numberIterationsAllowed));
5100	model->setNumberAnalyzeIterations(numberIterationsAllowed);
5101	if (numberToFix>0) {
5102	sprintf(general,"%d variable bounds modified by initial strong branching (%.2f seconds - %d iterations)",numberToFix,model->getCurrentSeconds()-time1,saveAllowed-numberIterationsAllowed);
5103	} else if (numberToFix<0) {
5104	sprintf(general,"initial strong branching found to be infeasible (%.2f seconds - %d iterations)",model->getCurrentSeconds()-time1,saveAllowed-numberIterationsAllowed);
5105	} else if ((solveType&32)!=0) {
5106	sprintf(general,"No variables fixed by initial strong branching (%.2f seconds - %d iterations)",model->getCurrentSeconds()-time1,saveAllowed-numberIterationsAllowed);
5107	} else {
5108	general[0]='\0';
5109	}
5110	if (general[0]!='\0')
5111	model->messageHandler()->message(CBC_GENERAL, *model->messagesPointer())
5112	<< general
5113	<< CoinMessageEol;
5114	double smallestEffect=COIN_DBL_MAX;
5115	double largestEffect=0.0;
5116	for (i = 0; i < numberIntegers; i++) {
5117	int iColumn=integerVariable[i];
5118	if (back[iColumn]>=numberColumns)
5119	continue;
5120	smallestEffect = CoinMin(smallestEffect,interAction[i]);
5121	largestEffect = CoinMax(largestEffect,interAction[i]);
5122	}
5123	double groupValue[11];
5124	int groupCounts[11]={0,0,0,0,0,0,0,0,0,0,0};
5125	groupValue[10]=largestEffect;
5126	for (int i=0;i<10;i++)
5127	groupValue[i]=smallestEffect+i0.1(largestEffect-smallestEffect);
5128	sprintf(general,"Looked at %d integer variables - smallest interaction %g",
5129	numberLookIntegers,smallestEffect);
5130	model->messageHandler()->message((solveType&32)==0 ? CBC_FPUMP2 : CBC_FPUMP1,
5131	*model->messagesPointer())
5132	<< general
5133	<< CoinMessageEol;
5134	for (int i = 0; i < numberIntegers; i++) {
5135	int iColumn=integerVariable[i];
5136	if (back[iColumn]>=numberColumns)
5137	continue;
5138	double value = interAction[i];
5139	int j;
5140	for (j=0;j<11;j++) {
5141	if (value<=groupValue[j]\|\|j==10)
5142	break;
5143	}
5144	groupCounts[j]++;
5145	}
5146	general[0]='\0';
5147	for (int i=0;i<11;i++)
5148	sprintf(general+strlen(general),"%d <= %g ",groupCounts[i],groupValue[i]);
5149	model->messageHandler()->message((solveType&32)==0 ? CBC_FPUMP2 : CBC_FPUMP1,
5150	*model->messagesPointer())
5151	<< general
5152	<< CoinMessageEol;
5153	smallestEffect=COIN_DBL_MAX;
5154	largestEffect=0.0;
5155	int numberChanged=0;
5156	int numberZeroMoved=0;
5157	for (i = 0; i < numberIntegers; i++) {
5158	int iColumn=integerVariable[i];
5159	if (back[iColumn]>=numberColumns)
5160	continue;