ILOG CPLEX 11.0 User's Manual

similar to the C++ goals and callbacks.) Goals and callbacks allow you to control thesolution process when solving MIPs based on information generated during the solutionprocess itself. Goals and Callbacks: a Comparison on page 469 contrasts the advantages ofboth.More Solution InformationDepending on the model being solved and the algorithm being used, more solutioninformation is generated in addition to the objective value and solution values for variablesand slacks. The following sections explain how to access that additional information.◆ Writing Solution Files on page 88◆ Dual Solution Information on page 88◆ Basis Information on page 89◆ Writing Solution Files on page 88◆ Infeasible Solution Information on page 89◆ Solution Quality on page 90Writing Solution FilesThe class IloCplex offers a variety of ways to write information about a solution that it hasfound.After solving, you can call the method IloCplex.writeMIPstart to write a MIP basissuitable for a restart. The file it writes is in MST format. That format is documented in thereference manual ILOG CPLEX File Formats.The method IloCplex.exportModel writes the active model to a file. The format of thefile depends on the file extension in the name of the file that your application passes as anargument to this method. A model exported in this way to a file can be read back intoILOG CPLEX by means of the method IloCplex.importModel. Both these methods aredocumented more fully in the reference manual of the Java API.Dual Solution InformationWhen solving an LP or QP, all the algorithms also compute dual solution information thatyour application can then query. (However, no dual information is available for QCPmodels.) You can access reduced costs by calling the method IloCplex.getReducedCostor IloCplex.getReducedCosts. Similarly, you can access dual solution values for theranged constraints of the active model by using the methods IloCplex.getDual orIloCplex.getDuals.88 ILOG CPLEX 11.0 — USER’ S MANUAL