An important observation to make here is that IloCplex is not really 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 algorithms, 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 individually selected and 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.

For linear programming problems (LPs), that is, models without integer, boolean or semi-continuous variables, without piecewise linear functions, without a quadratic component in the objective function, and without SOS, a variety of additional solution information can be queried. This includes 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 allows you to analyze the source of the infeasibility.