Introduction

Abstract

During the last thirty years there has been a growing interest in problem solving systems based on principles of evolution and hereditary: such systems maintain a population of potential solutions, they have some selection process based on fitness of individuals, and some recombination operators. One type of such systems is a class of Evolution Strategies i.e., algorithms which imitate the principles of natural evolution for parameter optimization problems [149], [162] (Rechenberg, Schwefel). Fogel’s Evolutionary Programming [57] is a technique for searching through a space of small finite-state machines. Glover’s Scatter Search techniques [64] maintain a population of reference points and generate offspring by weighted linear combinations. Another type of evolution based systems are Holland’s Genetic Algorithms (GAs) [89]. In 1990, Koza [108] proposed an evolution based system to search for the most fit computer program to solve a particular problem.

Again I saw that under the sun the race is not to the swift, nor the battle to the strong, nor bread to the wise, nor riches to the intelligent, nor favor to the man of skill; but time and chance happen to them all.

The Bible, Ecclesiastes, 9