Abstract:
We show how recent developments in mixed integer programming, both linear and nonlinear, have been used in improving software for solving mixed integer nonlinear programming (MINLP) problems. Examples of those developments are preprocessing, probing, callbacks and new heuristics. We demonstrate the benefits by using some real-life problems.