Evolutionary Computation

Introduction

Evolutionary Algorithms are stochastic population based search methods. They are gleaned from evolution theory (Darwin, Mendel) and from breeding theory (Lush, Falconer), respectively. They generate by an interplay of genetic or phenotypic variance and selection new and more adapted solutions.

Standard instances of Evolutionary Algorithms are (Bäck, Fogel, Michalewicz: Handbook of Evolutionary Computation. Oxford University Press 1997)Further algorithmic approaches were derived

Application

Evolutionary Algorithms are a rather young field of Computational Intelligence. But, a lot of applications for hard to solve industrial applications can be found.

Quantitative Genetics and Evolutionary Algorithms

A correspondence of Evolutionary Algorithms to early works in statistics and quantitative genetics is presented by the following tutorial:

H.-M. Voigt Introduction to Quantitative Genetics with Applications to Evolutionary Computation. Tutorial presented at the Fifth International Conference on Parallel Problem Solving from Nature (PPSN V). Amsterdam, 27 September 1998

Selected publications


© 1994- Hans-Michael Voigt
 
Hans-Michael Voigt
Evolutionary Computation
& Generative Art