Introduction

Abstract

Global optimization refers to a mathematical program, which seeks a maximum or minimum objective function value over a set of feasible solutions. The adjective “global” indicates that the optimization problem may be very general in nature; the objective function may be nonconvex, nondifferentiable, and possibly discontinuous over a continuous or discrete domain. A global optimization problem with continuous variables may contain several local optima or stationary points. The problem of designing algorithms that obtain global solutions is very difficult when there is no overriding structure that indicates whether a local solution is indeed the global solution.