ILOG CPLEX C++ API 9.0 Reference Manual

Refer to the ILOG Concert Technology Reference Manual for more information about
these classes.
IloCplex Optimizer Options
An instance of the class IloCplex is not really only one algorithm, but, in fact,
consists of a set of highly configurable algorithms, also known as optimizer options.
They include primal and dual simplex algorithms, barrier algorithm, a sifting algorithm,
a network simplex algorithm, and a branch & cut algorithm for MIPs. Though in most
cases IloCplex can be used like a black box, the optimizer options can be selected
individually to provide a wealth of parameters that allow you to fine tune the algorithm
to your particular model. In the case of the mixed integer optimizer, you can use your
own goals or callbacks and directly control the branch & cut search carried out by
IloCplex.
The most general kind of problem is a MIP. You might think of the LPs as a subset of
MIPs: an LP is a problem in which the model is:
◆ without integer variables,
◆ without Boolean variables,
◆ without semi-continuous variables,
◆ without piecewise linear functions,
◆ without a quadratic component in the objective function,
◆ without quadratic constraints,
◆ and without a special ordered set (SOS).
For linear programming problems (LPs), a variety of additional solution information can
be queried. These queries include dual information or, with the appropriate optimizer
option, basis information. Sensitivity analysis allows you to analyze how you can
modify your model while preserving the same solution. Or, if your model is infeasible,
the infeasibility finder enables you to analyze the source of the infeasibility.
ILOG CPLEX C++ API 9.0 REFERENCE M ANUAL 17