Changeset 9511


Ignore:
Timestamp:
Dec 20, 2014 5:26:33 PM (4 years ago)
Author:
gahacke
Message:

more pysp baseline updates

Location:
pyomo/trunk/pyomo/pysp/tests/unit
Files:
4 edited

Legend:

Unmodified
Added
Removed
  • pyomo/trunk/pyomo/pysp/tests/unit/networkflow1ef10_quadratic_cplex.baseline-a

    r9239 r9511  
    1616Initiating PH iteration=1
    1717WW PH Extension: Setting mipgap to 0.1000000, as specified in the configuration file
     18WW PH Extension: Analyzing variables for fixing
    1819Sub-problem solve time statistics - Min: 0.55 Avg: 0.89 Max: 1.22 (seconds)
    1920Number of discrete variables fixed=14 (total=30)
     
    2425Initiating PH iteration=2
    2526WW PH Extension: Setting mipgap to 0.0914664, based on current value of the convergence metric
     27WW PH Extension: Analyzing variables for fixing
    2628Sub-problem solve time statistics - Min: 0.54 Avg: 0.91 Max: 1.19 (seconds)
    2729Number of discrete variables fixed=16 (total=30)
     
    3234Initiating PH iteration=3
    3335WW PH Extension: Setting mipgap to 0.0829139, based on current value of the convergence metric
     36WW PH Extension: Analyzing variables for fixing
    3437Sub-problem solve time statistics - Min: 0.58 Avg: 0.77 Max: 1.06 (seconds)
    3538Number of discrete variables fixed=18 (total=30)
     
    4043Initiating PH iteration=4
    4144WW PH Extension: Setting mipgap to 0.0844544, based on current value of the convergence metric
     45WW PH Extension: Analyzing variables for fixing
    4246Sub-problem solve time statistics - Min: 0.54 Avg: 0.69 Max: 0.91 (seconds)
    4347Number of discrete variables fixed=20 (total=30)
     
    4852Initiating PH iteration=5
    4953WW PH Extension: Setting mipgap to 0.0026437, based on current value of the convergence metric
     54WW PH Extension: Analyzing variables for fixing
    5055Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    5156Number of discrete variables fixed=30 (total=30)
     
    5661Initiating PH iteration=6
    5762WW PH Extension: Setting mipgap to 0.0024072, based on current value of the convergence metric
     63WW PH Extension: Analyzing variables for fixing
    5864Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    5965Number of discrete variables fixed=30 (total=30)
     
    6470Initiating PH iteration=7
    6571WW PH Extension: Setting mipgap to 0.0021062, based on current value of the convergence metric
     72WW PH Extension: Analyzing variables for fixing
    6673Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    6774Number of discrete variables fixed=30 (total=30)
     
    7279Initiating PH iteration=8
    7380WW PH Extension: Setting mipgap to 0.0018984, based on current value of the convergence metric
     81WW PH Extension: Analyzing variables for fixing
    7482Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    7583Number of discrete variables fixed=30 (total=30)
     
    8088Initiating PH iteration=9
    8189WW PH Extension: Setting mipgap to 0.0015729, based on current value of the convergence metric
     90WW PH Extension: Analyzing variables for fixing
    8291Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    8392Number of discrete variables fixed=30 (total=30)
     
    8897Initiating PH iteration=10
    8998WW PH Extension: Setting mipgap to 0.0014255, based on current value of the convergence metric
     99WW PH Extension: Analyzing variables for fixing
    90100Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    91101Number of discrete variables fixed=30 (total=30)
     
    96106Initiating PH iteration=11
    97107WW PH Extension: Setting mipgap to 0.0012691, based on current value of the convergence metric
     108WW PH Extension: Analyzing variables for fixing
    98109Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    99110Number of discrete variables fixed=30 (total=30)
     
    104115Initiating PH iteration=12
    105116WW PH Extension: Setting mipgap to 0.0011411, based on current value of the convergence metric
     117WW PH Extension: Analyzing variables for fixing
    106118Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    107119Number of discrete variables fixed=30 (total=30)
     
    112124Initiating PH iteration=13
    113125WW PH Extension: Setting mipgap to 0.0011195, based on current value of the convergence metric
     126WW PH Extension: Analyzing variables for fixing
    114127Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    115128Number of discrete variables fixed=30 (total=30)
     
    120133Initiating PH iteration=14
    121134WW PH Extension: Setting mipgap to 0.0009845, based on current value of the convergence metric
     135WW PH Extension: Analyzing variables for fixing
    122136Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    123137Number of discrete variables fixed=30 (total=30)
     
    128142Initiating PH iteration=15
    129143WW PH Extension: Setting mipgap to 0.0008688, based on current value of the convergence metric
     144WW PH Extension: Analyzing variables for fixing
    130145Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    131146Number of discrete variables fixed=30 (total=30)
     
    136151Initiating PH iteration=16
    137152WW PH Extension: Setting mipgap to 0.0007948, based on current value of the convergence metric
     153WW PH Extension: Analyzing variables for fixing
    138154Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    139155Number of discrete variables fixed=30 (total=30)
     
    144160Initiating PH iteration=17
    145161WW PH Extension: Setting mipgap to 0.0007657, based on current value of the convergence metric
     162WW PH Extension: Analyzing variables for fixing
    146163Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    147164Number of discrete variables fixed=30 (total=30)
     
    152169Initiating PH iteration=18
    153170WW PH Extension: Setting mipgap to 0.0006689, based on current value of the convergence metric
     171WW PH Extension: Analyzing variables for fixing
    154172Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    155173Number of discrete variables fixed=30 (total=30)
     
    160178Initiating PH iteration=19
    161179WW PH Extension: Setting mipgap to 0.0005749, based on current value of the convergence metric
     180WW PH Extension: Analyzing variables for fixing
    162181Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    163182Number of discrete variables fixed=30 (total=30)
     
    168187Initiating PH iteration=20
    169188WW PH Extension: Setting mipgap to 0.0005117, based on current value of the convergence metric
     189WW PH Extension: Analyzing variables for fixing
    170190Sub-problem solve time statistics - Min: 0.02 Avg: 0.02 Max: 0.02 (seconds)
    171191Number of discrete variables fixed=30 (total=30)
  • pyomo/trunk/pyomo/pysp/tests/unit/sizes10_quadratic_twobundles_cplex.baseline-a

    r8715 r9511  
    11Initializing PH
    22
    3 WARNING: No construction rule or expression specified for constraint 'MASTER_BLEND_CONSTRAINT_RootNode'
    4 WARNING: No construction rule or expression specified for constraint 'MASTER_BLEND_CONSTRAINT_RootNode'
    53Starting PH
    64
     
    311309
    312310
    313 
    314 
    315311Total execution time=34.76 seconds
  • pyomo/trunk/pyomo/pysp/tests/unit/sizes10_quadratic_twobundles_cplex.baseline-b

    r8715 r9511  
    3939   Stage: FirstStage
    4040          (Scenarios: Scenario1  Scenario2  Scenario3  Scenario4  Scenario5  Scenario6  Scenario7  Scenario8  Scenario9  Scenario10  )
     41      Variable: NumProducedFirstStage
     42         Index:  [3]    Values:    34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000    Max-Min:        0.0000    Avg:    34875.0000
     43         Index:  [5]    Values:    47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000    Max-Min:        0.0000    Avg:    47500.0000
     44         Index:  [6]    Values:    47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000    Max-Min:        0.0000    Avg:    47250.0000
     45         Index:  [8]    Values:    43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000    Max-Min:        0.0000    Avg:    43250.0000
     46         Index: [10]    Values:    27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000    Max-Min:        0.0000    Avg:    27125.0000
     47          (Scenarios: Scenario1  Scenario2  Scenario3  Scenario4  Scenario5  Scenario6  Scenario7  Scenario8  Scenario9  Scenario10  )
    4148      Variable: NumUnitsCutFirstStage
    4249         Index:   [3,1] Values:     2500.0000   2500.0000   2500.0000   2500.0000   2500.0000   2500.0000   2500.0000   2500.0000   2500.0000   2500.0000    Max-Min:        0.0000    Avg:     2500.0000
     
    5057         Index:  [10,9] Values:    12500.0000  12500.0000  12500.0000  12500.0000  12500.0000  12500.0000  12500.0000  12500.0000  12500.0000  12500.0000    Max-Min:        0.0000    Avg:    12500.0000
    5158         Index: [10,10] Values:     5000.0000   5000.0000   5000.0000   5000.0000   5000.0000   5000.0000   5000.0000   5000.0000   5000.0000   5000.0000    Max-Min:        0.0000    Avg:     5000.0000
    52           (Scenarios: Scenario1  Scenario2  Scenario3  Scenario4  Scenario5  Scenario6  Scenario7  Scenario8  Scenario9  Scenario10  )
    53       Variable: NumProducedFirstStage
    54          Index:  [3]    Values:    34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000  34875.0000    Max-Min:        0.0000    Avg:    34875.0000
    55          Index:  [5]    Values:    47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000  47500.0000    Max-Min:        0.0000    Avg:    47500.0000
    56          Index:  [6]    Values:    47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000  47250.0000    Max-Min:        0.0000    Avg:    47250.0000
    57          Index:  [8]    Values:    43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000  43250.0000    Max-Min:        0.0000    Avg:    43250.0000
    58          Index: [10]    Values:    27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000  27125.0000    Max-Min:        0.0000    Avg:    27125.0000
    5959          (Scenarios: Scenario1  Scenario2  Scenario3  Scenario4  Scenario5  Scenario6  Scenario7  Scenario8  Scenario9  Scenario10  )
    6060      Variable: ProduceSizeFirstStage
  • pyomo/trunk/pyomo/pysp/tests/unit/sizes3_ef_with_solve_cplex.baseline-a

    r9430 r9511  
    9898Scenario-based instance initialization enabled
    9999Creating instance for scenario=Scenario1
    100 Data for scenario=Scenario1 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.6_carr/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario1.dat
     100Data for scenario=Scenario1 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.7_with_acro/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario1.dat
    101101Creating instance for scenario=Scenario2
    102 Data for scenario=Scenario2 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.6_carr/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario2.dat
     102Data for scenario=Scenario2 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.7_with_acro/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario2.dat
    103103Creating instance for scenario=Scenario3
    104 Data for scenario=Scenario3 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.6_carr/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario3.dat
    105 Time to construct scenario instances=0.10 seconds
     104Data for scenario=Scenario3 loads from file=/home/hudson/slave/workspace/Pyomo_trunk_python2.7_with_acro/src/pyomo.pysp/examples/pysp/sizes/SIZES3//Scenario3.dat
     105Time to construct scenario instances=0.06 seconds
    106106Creating extensive form binding instance
    107107Creating variables for master binding instance
    108 Time to construct extensive form instance=0.02 seconds
    109 Time to create the extensive form=0.12 seconds
     108Time to construct extensive form instance=0.01 seconds
     109Time to create the extensive form=0.07 seconds
    110110Queuing extensive form solve
    111 Solver script file=/tmp/tmpkVosco.cplex.script
    112 Solver log file: '/tmp/tmpamIdxx.cplex.log'
    113 Solver solution file: '/tmp/tmpmsWjeq.cplex.sol'
    114 Solver problem files: ('/tmp/tmpIdH7kE.pyomo.lp',)
     111Solver script file=/tmp/tmpFADxOn.cplex.script
     112Solver log file: '/tmp/tmp0OXuHv.cplex.log'
     113Solver solution file: '/tmp/tmpfF5jmf.cplex.sol'
     114Solver problem files: ('/tmp/tmpNWcPUy.pyomo.lp',)
    115115Waiting for extensive form solve
    116 Output file written to file= /home/hudson/slave/workspace/Pyomo_trunk_python2.6_carr/src/pyomo.pysp/pyomo/pysp/tests/unit/test_sizes3_ef.lp
    117 Time to solve and load results for the extensive form=0.48 seconds
     116Output file written to file= /home/hudson/slave/workspace/Pyomo_trunk_python2.7_with_acro/src/pyomo.pysp/pyomo/pysp/tests/unit/test_sizes3_ef.lp
     117Time to solve and load results for the extensive form=0.32 seconds
    118118
    119119***********************************************************************************************
     
    131131                NumProducedFirstStage[3]=38250.0
    132132                NumProducedFirstStage[5]=45000.0
    133                 NumProducedFirstStage[6]=50000.0
    134                 NumProducedFirstStage[8]=42749.9999999
     133                NumProducedFirstStage[6]=49500.0
     134                NumProducedFirstStage[8]=43250.0
    135135                NumProducedFirstStage[10]=24000.0
    136136                NumUnitsCutFirstStage[3,1]=2500.0
     
    141141                NumUnitsCutFirstStage[6,6]=25000.0
    142142                NumUnitsCutFirstStage[8,7]=15000.0
    143                 NumUnitsCutFirstStage[8,8]=12500.0000001
     143                NumUnitsCutFirstStage[8,8]=12500.0
    144144                NumUnitsCutFirstStage[10,9]=12500.0
    145145                NumUnitsCutFirstStage[10,10]=5000.0
     
    154154        Parent=RootNode
    155155        Variables:
    156                 NumProducedSecondStage[5]=24000.0
    157                 NumProducedSecondStage[9]=9750.0
     156                NumProducedSecondStage[5]=24500.0
     157                NumProducedSecondStage[9]=9250.0
    158158                NumUnitsCutSecondStage[3,1]=1750.0
    159159                NumUnitsCutSecondStage[3,2]=5250.0
    160160                NumUnitsCutSecondStage[3,3]=8750.0
    161                 NumUnitsCutSecondStage[5,5]=24000.0
     161                NumUnitsCutSecondStage[5,5]=24500.0
    162162                NumUnitsCutSecondStage[6,4]=7000.0
    163                 NumUnitsCutSecondStage[6,5]=500.0
    164163                NumUnitsCutSecondStage[6,6]=17500.0
    165                 NumUnitsCutSecondStage[8,7]=6500.0
    166                 NumUnitsCutSecondStage[8,8]=8750.00000007
    167                 NumUnitsCutSecondStage[9,7]=1000.0
     164                NumUnitsCutSecondStage[8,7]=7000.0
     165                NumUnitsCutSecondStage[8,8]=8750.0
     166                NumUnitsCutSecondStage[9,7]=500.0
    168167                NumUnitsCutSecondStage[9,9]=8750.0
    169168                NumUnitsCutSecondStage[10,7]=3000.0
     
    184183                NumUnitsCutSecondStage[5,4]=10000.0
    185184                NumUnitsCutSecondStage[5,5]=35000.0
    186                 NumUnitsCutSecondStage[6,6]=25000.0
    187                 NumUnitsCutSecondStage[8,7]=2750.0
    188                 NumUnitsCutSecondStage[8,8]=12500.0000001
     185                NumUnitsCutSecondStage[6,6]=24500.0
     186                NumUnitsCutSecondStage[8,6]=500.0
     187                NumUnitsCutSecondStage[8,7]=2749.99999998
     188                NumUnitsCutSecondStage[8,8]=12500.0
    189189                NumUnitsCutSecondStage[9,7]=10750.0
    190190                NumUnitsCutSecondStage[9,9]=12500.0
     
    192192                NumUnitsCutSecondStage[10,10]=5000.0
    193193                ProduceSizeSecondStage[5]=1.0
    194                 ProduceSizeSecondStage[9]=1.0
     194                ProduceSizeSecondStage[9]=0.999999999992
    195195
    196196        Name=Scenario3Node
     
    200200                NumProducedSecondStage[2]=13000.0
    201201                NumProducedSecondStage[5]=59000.0
    202                 NumProducedSecondStage[7]=27000.0000001
    203                 NumProducedSecondStage[9]=17250.0000001
     202                NumProducedSecondStage[7]=27500.0000001
     203                NumProducedSecondStage[9]=16750.0
    204204                NumUnitsCutSecondStage[2,1]=3250.0
    205205                NumUnitsCutSecondStage[2,2]=9750.0
     
    208208                NumUnitsCutSecondStage[5,4]=13000.0
    209209                NumUnitsCutSecondStage[5,5]=45500.0
    210                 NumUnitsCutSecondStage[6,6]=25000.0
    211                 NumUnitsCutSecondStage[7,6]=7500.0
     210                NumUnitsCutSecondStage[6,6]=24500.0
     211                NumUnitsCutSecondStage[7,6]=8000.0
    212212                NumUnitsCutSecondStage[7,7]=19500.0000001
    213                 NumUnitsCutSecondStage[8,8]=15250.0
    214                 NumUnitsCutSecondStage[9,8]=1000.0
     213                NumUnitsCutSecondStage[8,8]=15750.0
     214                NumUnitsCutSecondStage[9,8]=500.0
    215215                NumUnitsCutSecondStage[9,9]=16250.0
    216216                NumUnitsCutSecondStage[10,10]=6500.0
     
    218218                ProduceSizeSecondStage[5]=1.0
    219219                ProduceSizeSecondStage[7]=1.0
    220                 ProduceSizeSecondStage[9]=0.999999999998
    221 
     220                ProduceSizeSecondStage[9]=0.999999999994
    222221
    223222Extensive form costs:
     
    249248        Scenarios:
    250249                Scenario1
    251         Expected cost of (sub)tree rooted at node=28160.6000
     250        Expected cost of (sub)tree rooted at node=28135.8000
    252251
    253252        Name=Scenario2Node
     
    259258        Scenarios:
    260259                Scenario2
    261         Expected cost of (sub)tree rooted at node=61373.2000
     260        Expected cost of (sub)tree rooted at node=61377.2000
    262261
    263262        Name=Scenario3Node
     
    269268        Scenarios:
    270269                Scenario3
    271         Expected cost of (sub)tree rooted at node=94678.6000
     270        Expected cost of (sub)tree rooted at node=94668.2000
    272271
    273272----------------------------------------------------
     
    280279                RootNode
    281280                Scenario1Node
    282         Stage=          FirstStage     Cost=162871.2000
    283         Stage=         SecondStage     Cost=28160.6000
    284         Total scenario cost=191031.8000
     281        Stage=          FirstStage     Cost=162881.6000
     282        Stage=         SecondStage     Cost=28135.8000
     283        Total scenario cost=191017.4000
    285284
    286285        Name=Scenario2
     
    290289                RootNode
    291290                Scenario2Node
    292         Stage=          FirstStage     Cost=162871.2000
    293         Stage=         SecondStage     Cost=61373.2000
    294         Total scenario cost=224244.4000
     291        Stage=          FirstStage     Cost=162881.6000
     292        Stage=         SecondStage     Cost=61377.2000
     293        Total scenario cost=224258.8000
    295294
    296295        Name=Scenario3
     
    300299                RootNode
    301300                Scenario3Node
    302         Stage=          FirstStage     Cost=162871.2000
    303         Stage=         SecondStage     Cost=94678.6000
     301        Stage=          FirstStage     Cost=162881.6000
     302        Stage=         SecondStage     Cost=94668.2000
    304303        Total scenario cost=257549.8000
    305304
    306305----------------------------------------------------
    307 Total execution time=0.60 seconds
     306Total execution time=0.39 seconds
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