Choose an Optimizer

ILOG CPLEX 11.0 User's Manual > Programming Considerations > Developing CPLEX Applications > Tips for Successful Application Development > Choose an Optimizer

Choose an Optimizer

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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:

Use the primal simplex, dual simplex, or primal-dual barrier optimizers to solve linear and quadratic programs.
Use the barrier optimizer to solve quadratically constrained programming problems.
The network optimizer is appropriate for solving linear and quadratic programs with large embedded networks.
Use the MIP optimizer if the problem contains discrete components (binary, integer, or semi-continuous variables, piecewise linear objective, or SOS sets).

In ILOG CPLEX, there are many possible parameter settings for each optimizer. Generally, the default parameter settings are best for linear programming and quadratic programming problems, but Solving LPs: Simplex Optimizers and Solving Problems with a Quadratic Objective (QP) offer more detail about improving performance with respect to these problems. Integer programming problems are more sensitive to specific parameter settings, so you may need to experiment with them, as suggested in Solving Mixed Integer Programming Problems (MIP).

In either case, the Interactive Optimizer in ILOG CPLEX lets you try different parameter settings and different optimizers to decide 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.

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