Choose an optimizer

According to problem type, consider which optimizer to use.

After a problem object has been instantiated and populated, it can be solved using one of the optimizers provided by the CPLEX Callable Library. The choice of optimizer depends on the problem type.

• LP and QP problems can be solved by:

  • the primal simplex optimizer;

  • the dual simplex optimizer; and

  • the barrier optimizer.

• LP and QP problems with a substantial network can also be solved by a special network optimizer.

• LP problems can also be solved by:

  • the sifting optimizer; and

  • the concurrent optimizer.

• If the problem includes integer variables, mixed integer programming (MIP) must be used.

There are also many different possible parameter settings for each optimizer. The default values will usually be the best for linear programs. Integer programming problems are more sensitive to specific settings, so additional experimentation will often be useful.

Choosing the best way to solve the problem can dramatically improve performance. For more information, refer to the sections about tuning LP performance and trouble-shooting MIP performance in the CPLEX User’s Manual.