Penalty-Based Heuristic DIRECT Method for Constrained Global Optimization

Abstract

This paper is concerned with an extension of the heuristic DIRECT method, presented in [8], to solve nonlinear constrained global optimization (CGO) problems. Using a penalty strategy based on a penalty auxiliary function, the CGO problem is transformed into a bound constrained problem. We have analyzed the performance of the proposed algorithm using fixed values of the penalty parameter, and we may conclude that the algorithm competes favourably with other DIRECT-type algorithms in the literature.