After you have instantiated and populated a problem object, you solve it by calling one of the optimizers available in the ILOG CPLEX Component Libraries. Your choice of optimizer depends on the type of problem:

• If the problem is a linear program, use the linear optimizer.

• If the linear program includes a large embedded network, consider using the network optimizer.

• If the problem includes integer variables (MIP), use the branch & cut algorithm (implemented in the separately licensed ILOG CPLEX Mixed Integer Optimizer).

• If the problem is a convex quadratic program (QP), use the primal-dual barrier method (implemented in the separately licensed ILOG CPLEX Barrier Optimizer).

In ILOG CPLEX, there are many possible parameter settings for each optimizer. Generally, the default parameter settings are best for linear programming problems, but Chapter 4, Solving Linear Programming Problems, offers more detail about improving performance with respect to LP problems. Integer programming problems are more sensitive to specific parameter settings, so you may need to experiment with them, as suggested in Chapter 5, Solving Mixed Integer Programming Problems.

In either case, the Interactive Optimizer in ILOG CPLEX lets you try different parameter settings and different optimizers to determine the best optimization procedure for your particular application. From what you learn by experimenting with commands in the Interactive Optimizer, you can more readily choose which method or routine from the Component Libraries to call in your application.