Nonsmooth optimization through Mesh Adaptive Direct Search and Variable Neighborhood Search

Abstract

This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm, which extends the Generalized Pattern Search (GPS) algorithm, with the Variable Neighborhood Search (VNS) metaheuristic, for nonsmooth constrained optimization. The resulting algorithm retains the convergence properties of MADS, and allows the far reaching exploration features of VNS to move away from local solutions. The paper also proposes a generic way to use surrogate functions in the VNS search. Numerical results illustrate advantages and limitations of this method.