Introduction

Abstract

Evolutionary algorithms (EAs) are biologically inspired, randomized search meta-heuristics. They unify the fundamental principles of biological evolution: inheritance of genes, variation of genes in a population, translation of genotype into phenotype and selection of the fittest in the sense of the Darwinian principle survival of the fittest [28]. In the sixties Holland, Rechenberg and Schwefel translated this paradigm of evolution into a concept of algorithms which is called evolutionary computation (EC). Today, this computational method has grown to a rich and frequently used optimization method. It comprises several variants of algorithms which are structurally similar, but specialized to certain search domain characteristics.