View source for Natural selection in search and computation

''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 <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/n/n120/n120050/n1200501.png" /> data structures <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/n/n120/n120050/n1200502.png" /> 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>