View source for 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|Genetic algorithm]]); evolutionary strategies; evolutionary programming; genetic programming. Such algorithms and ideas have found many applications in, e.g.: [[Scheduling theory|scheduling theory]]; circuit and network design; architectural design; control (cf. [[Control system|Control system]]); signal processing; selection of most reliable populations (in [[Statistics|statistics]]); optimal treatment (in statistics); production planning; etc.

====References====
<table><tr><td valign="top">[a1]</td> <td valign="top">  N.K. Bansal,   S. Gupta,   "On the natural selection rule in general linear models"  ''Metrika'' , '''46'''  (1997)  pp. 59–69</td></tr><tr><td valign="top">[a2]</td> <td valign="top">  "Evolutionary algorithms in engineering applications"  D. Dasgupta (ed.)  Z. Michalewicz (ed.) , Springer  (1997)</td></tr><tr><td valign="top">[a3]</td> <td valign="top">  D.E. Goldberg,   "Genetic algorithms in search, optimization and machine learning" , Addison-Wesley  (1989)</td></tr><tr><td valign="top">[a4]</td> <td valign="top">  J.R. Koza,   "Genetic programming: on the programming of computers by means of natural selection and genetics" , MIT  (1992)</td></tr><tr><td valign="top">[a5]</td> <td valign="top">  Z. Michalewicz,   "Genetic algorithms $+$ data structures $=$ evolution programs" , Springer  (1992)</td></tr><tr><td valign="top">[a6]</td> <td valign="top">  L.C. Tang,   "A nonparametric approach for selecting the most reliable population"  ''Queueing Systems'' , '''24'''  (1996)  pp. 169–176</td></tr></table>