ILOG CPLEX 11.0 User's Manual > Continuous Optimization > Solving LPs: Simplex Optimizers > Diagnosing LP Infeasibility > Repairing Infeasibility: FeasOpt

Previous sections focused on how to diagnose the causes of infeasibility. However, you may want to go beyond diagnosis to perform automatic correction of your model and then proceed with delivering a solution. One approach for doing so is to build your model with explicit slack variables and other modeling constructs, so that an infeasible outcome is never a possibility. Such techniques for formulating a model are beyond the scope of this discussion, but you should consider them if you want the greatest possible flexibility in your application.

In contrast, an automated approach offered in ILOG CPLEX is known as FeasOpt (for feasible optimization). FeasOpt attempts to repair an infeasibility by modifying the model according to preferences set by the user. For more about this approach, see Repairing Infeasibilities with FeasOpt