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8 | Simplex-specific Methods |
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10 | Basic Model Classes |
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12 | Simplex-specific Methods |
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13 | </h2></div></div></div><p> |
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14 | Some of the most commonly-used methods when working with Simplex are listed in |
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15 | the table below. |
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16 | </p><div class="table"><a name="id4769539"></a><p class="title"><b>Table 2.3. Common Simplex-specific methods</b></p><table summary="Common Simplex-specific methods" border="0"><colgroup><col><col></colgroup><thead><tr><th> |
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17 | Method(s) |
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18 | </th><th> |
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19 | Description |
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20 | </th></tr></thead><tbody><tr><td align="left" valign="top"> |
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21 | <tt class="function">primal(int mode=0)</tt> |
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22 | </td><td align="left" valign="top"> |
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23 | This applies the primal algorithm. If <i class="parameter"><tt>mode</tt></i> is |
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24 | set to the default of 0, then the method uses the status variables to |
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25 | determine basis and solution. If <i class="parameter"><tt>mode</tt></i> is 1 then |
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26 | the method does a values pass so variables not in basis are given their |
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27 | current values and one pass of variables is done to clean up the basis |
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28 | with an equal or better objective value. |
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29 | </td></tr><tr><td align="left" valign="top"> |
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30 | <tt class="function">dual(int mode=0)</tt> |
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31 | </td><td align="left" valign="top"> |
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32 | This applies the dual algorithm. if <i class="parameter"><tt>mode</tt></i> is set |
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33 | to the default of 0, then the method uses the status variables to |
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34 | determine basis and solution. If <i class="parameter"><tt>mode</tt></i> is 1 then |
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35 | the method uses input duals and does a values pass so one pass of basic |
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36 | variables is done to clean up the duals with an equal or better objective |
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37 | value. |
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38 | </td></tr><tr><td align="left" valign="top"> |
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39 | <tt class="function">scaling(int mode=1)</tt> |
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40 | </td><td align="left" valign="top"> |
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41 | This method toggles scaling on (<i class="parameter"><tt>mode</tt></i> set to 1) |
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42 | and off (<i class="parameter"><tt>mode</tt></i> set to 0). |
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43 | </td></tr><tr><td align="left" valign="top"> |
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44 | <tt class="function">int crash(double gap,int mode)</tt> |
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45 | </td><td align="left" valign="top"> |
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46 | This method attemps to improve on an all slack basis. |
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47 | For dual this will move variables to the dual feasible bound |
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48 | if the gap between bounds is less than <i class="parameter"><tt>gap</tt></i>. Setting |
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49 | <i class="parameter"><tt>mode</tt></i> to 0 guesses which algorithm is better, while |
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50 | a value of 1 or 2 will result in more work being done. The return code is |
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51 | 0 if the basis was not slacks in first case, it is negative if dual is |
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52 | preferred or positive if primal. ±1 means an all slack basis seemed |
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53 | best, while ±2 means some work was done. |
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54 | </td></tr><tr><td align="left" valign="top"> |
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55 | <tt class="function">perturb(int mode)</tt> |
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56 | </td><td align="left" valign="top"> |
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57 | This method toggles perturbation on (<i class="parameter"><tt>mode</tt></i> set to 1) |
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58 | and off (<i class="parameter"><tt>mode</tt></i> set to 0). It should be considered |
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59 | a work in progress, although on some problems it gives very good results. |
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60 | </td></tr><tr><td align="left" valign="top"> |
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61 | <tt class="function">factorizationFrequency()</tt><br> |
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62 | <tt class="function">setFactorizationFrequency(int value)</tt> |
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63 | </td><td align="left" valign="top"> |
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64 | These are "get" and "set" methods for the basis matrix |
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65 | factorization frequency. The default is to refactor every 200 iterations, |
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66 | but it may make more sense to use something such as 100 + the number of |
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67 | rows divided by 50. |
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68 | </td></tr><tr><td align="left" valign="top"> |
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69 | <tt class="function">dualBound()</tt><br> |
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70 | <tt class="function">setDualBound(double value)</tt> |
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71 | </td><td align="left" valign="top"> |
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72 | These are "get" and "set" methods for the |
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73 | "dual bound". The CLP dual algorithm declares all problems |
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74 | to be dual feasible by putting non-basic variables to correct bounds for |
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75 | the reduced cost. If the gap between the bounds is too big then it |
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76 | pretends the gap is only the value specified by this set method. |
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77 | In essence, this gives a composite dual rather than a pure |
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78 | Phase I- Phase II method. |
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79 | </td></tr><tr><td align="left" valign="top"> |
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80 | <tt class="function">infeasibilityCost()</tt><br> |
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81 | <tt class="function">setInfeasibilityCost(double value)</tt> |
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82 | </td><td align="left" valign="top"> |
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83 | These are the primal analogs to the "dual bound" methods. |
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84 | </td></tr><tr><td align="left" valign="top"> |
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85 | <tt class="function">numberPrimalInfeasibilities()</tt><br> |
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86 | <tt class="function">sumPrimalInfeasibilities()</tt> |
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87 | </td><td align="left" valign="top"> |
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88 | After a solve, there may be infeasibilities. These methods serve to |
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89 | check for said infeasibilities. One could check the solution explicitly |
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90 | as well. For a code fragement illustrating this, see |
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91 | <a href="ch02s08.html#presolveexample" title="Example 2.3. Presolve code fragment">Example 2.3, “Presolve code fragment”</a>. |
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93 | Presolve |
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