Natural selection in search and computation

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evolutionary computation

An evolutionary algorithm is a general-purpose search procedure based on the mechanisms of natural selection and population genetics. Different variants are: genetic algorithms (cf. Genetic algorithm); evolutionary strategies; evolutionary programming; genetic programming. Such algorithms and ideas have found many applications in, e.g.: scheduling theory; circuit and network design; architectural design; control (cf. Control system); signal processing; selection of most reliable populations (in statistics); optimal treatment (in statistics); production planning; etc.


[a1] N.K. Bansal, S. Gupta, "On the natural selection rule in general linear models" Metrika , 46 (1997) pp. 59–69
[a2] "Evolutionary algorithms in engineering applications" D. Dasgupta (ed.) Z. Michalewicz (ed.) , Springer (1997)
[a3] D.E. Goldberg, "Genetic algorithms in search, optimization and machine learning" , Addison-Wesley (1989)
[a4] J.R. Koza, "Genetic programming: on the programming of computers by means of natural selection and genetics" , MIT (1992)
[a5] Z. Michalewicz, "Genetic algorithms $+$ data structures $=$ evolution programs" , Springer (1992)
[a6] L.C. Tang, "A nonparametric approach for selecting the most reliable population" Queueing Systems , 24 (1996) pp. 169–176
How to Cite This Entry:
Natural selection in search and computation. Encyclopedia of Mathematics. URL:
This article was adapted from an original article by M. Hazewinkel (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article