An exact penalty global optimization approach for mixed-integer programming problems

Stefano Lucidi, Francesco Rinaldi

Abstract: In this work, we propose a global optimization approach for mixed-integer programming problems. To this aim, we preliminarily define an exact penalty algorithm model for globally solving general problems and we show its convergence properties. Then, we describe a particular version of the algorithm that solves mixed-integer problems and we report computational results on some MINLP problems.