ILOG CPLEX 11.0 User's Manual > Discrete Optimization > Solving Mixed Integer Programming Problems (MIP) > Troubleshooting MIP Performance Problems

Even the most sophisticated methods currently available to solve pure integer and mixed integer programming problems require noticeably more computation than the methods for similarly sized continuous problems. Many relatively small integer programming models still take enormous amounts of computing time to solve. Indeed, some such models have never yet been solved. In the face of these practical obstacles to a solution, proper formulation of the model is crucial to successful solution of pure integer or mixed integer programs.

For help in formulating a model of your own integer or mixed integer problem, you may want to consult H.P. Williams's textbook about practical model building (referenced in Further Reading in the preface of this manual).

Also you may want to develop a better understanding of the branch & cut algorithm. For that purpose, Williams's book offers a good introduction, and Nemhauser and Wolsey's book (also referenced in Further Reading in the preface of this manual) goes into greater depth about branch & cut as well as other techniques implemented in the ILOG CPLEX MIP Optimizer.

Tuning Performance Features of the Mixed Integer Optimizer in this chapter has already discussed several specific features that are important for performance tuning of difficult models. Here are more specific performance symptoms and the remedies that can be tried.