Figure 4.51: The Network Tab in CPLEX Options Dialog Box
You can change the Network options for CPLEX by choosing CPLEX parameters from the Options menu and then pressing the Network tab. This will display the dialog box shown below:
Figure 4.51: The Network Tab in CPLEX Options Dialog Box
| Option Name | MPL Name | Solver Param | ParamNr | Type | Default | Min | Max |
|---|---|---|---|---|---|---|---|
| Pricing | NetSimplexPricingAlg | NetPPriIInd | 5004 | list | 0 | 0 | 3 |
| Network extraction | NetworkExtractLevel | NetFind | 1022 | list | 1 | 1 | 3 |
| Feasibility | NetPrimalFeasibleTol | NetEpRHS | 5003 | real | 1e-6 | 1e-11 | 1e-4 |
| Optimality | NetPrimalOptimalTol | NetEpOpt | 5002 | real | 1e-6 | 1e-11 | 1e-4 |
| Iteration Limit | NetSimplexIterLimit | NetItLim | 5001 | int | MAXINT | 0 | MAXINT |
The default (Automatic) shows best performance for most problems, and currently is equivalent to Multiple partial pricing with sorting.
The Network extraction option selects the level of network extraction for network simplex optimizations.
| Natural network only (1) | Only natural networks are extracted |
| Use reflection scaling (2) | Larger networks are extracted using reflection scaling. |
| Use general scaling (3) | Larger networks are extracted using general scaling. |
he feasibility tolerance specifies the degree to which a problem's flow value may violate its bounds. This tolerance influences the selection of an optimal basis and can be reset to a lower value when a problem is having difficulty maintaining feasibility during optimization. You may also wish to lower this tolerance after finding an optimal solution if there is any doubt that the solution is truly optimal. If the feasibility tolerance is set too low, CPLEX may falsely conclude that a problem is infeasible. If you encounter reports of infeasibility during Phase II of the optimization, a small adjustment in the feasibility tolerance may improve performance. The value can by any number between 0.0001 and le-11.
The optimality tolerance specifies the amount a reduced cost may violate the criterion for an optimal solution. The value can by any number between 0.0001 and le-11.
Sets the maximum number of iterations to be performed before the algorithm terminates without reaching optimality. The value can be any non-negative integer.