Genetic algorithms - a survey of models and methods

Darrell Whitley, Andrew M. Sutton

Research output: Chapter in Book/Report/Conference proceedingChapter

21 Scopus citations

Abstract

This chapter first reviews the simple genetic algorithm. Mathematical models of the genetic algorithm are also reviewed, including the schema theorem, exact infinite population models, and exact Markov models for finite populations. The use of bit representations, including Gray encodings and binary encodings, is discussed. Selection, including roulette wheel selection, rank-based selection, and tournament selection, is also described. This chapter then reviews other forms of genetic algorithms, including the steady-state Genitor algorithm and the CHC (cross-generational elitist selection, heterogenous recombination, and cataclysmic mutation) algorithm. Finally, landscape structures that can cause genetic algorithms to fail are looked at, and an application of genetic algorithms in the domain of resource scheduling, where genetic algorithms have been highly successful, is also presented.

Original languageEnglish (US)
Title of host publicationHandbook of Natural Computing
PublisherSpringer Berlin Heidelberg
Pages637-671
Number of pages35
Volume2-4
ISBN (Electronic)9783540929109
ISBN (Print)9783540929093
DOIs
StatePublished - Jan 1 2012

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