Memetic Algorithms in Discrete Optimization

Introduction

Discrete optimization concerns in essence the search for a “best” configuration (optimal solution) among a set of finite candidate configurations according to a particular criterion. There are several ways to describe a discrete optimization problem. In its most general form, it can be defined as a collection of problem instances, each being specified by a pair (S,f) [704], where S is the set of finite candidate configurations, defining the search space; f is the cost or objective function, given by a mapping f: S → R⁺.