Editing Crossover (evolutionary algorithm) (section)

{{short description|Operator used to vary the programming of chromosomes from one generation to the next}}
{{Evolutionary algorithms}}
'''Crossover''' in [[evolutionary algorithm]]s and [[evolutionary computation]], also called '''recombination''', is a [[genetic operator]] used to combine the [[chromosome (genetic algorithm)|genetic information]] of two parents to generate new offspring. It is one way to [[stochastic|stochastically]] generate new [[candidate solution|solutions]] from an existing population, and is analogous to the [[chromosomal crossover|crossover]] that happens during [[sexual reproduction]] in [[biology]]. New solutions can also be generated by [[cloning (programming)|cloning]] an existing solution, which is analogous to [[asexual reproduction]]. Newly generated solutions may be [[mutation (genetic algorithm)|mutated]] before being added to the population. The aim of recombination is to transfer good characteristics from two different parents to one child.

Different algorithms in evolutionary computation may use different data structures to store genetic information, and each [[genetic representation]] can be recombined with different crossover operators. Typical [[data structure|data structures]] that can be recombined with crossover are [[bit array|bit arrays]], vectors of real numbers, or [[tree (data structure)|trees]].

The list of operators presented below is by no means complete and serves mainly as an exemplary illustration of this dyadic [[genetic operator]] type. More operators and more details can be found in the literature.<ref name=":0">{{Cite book |title=Handbook of genetic algorithms |date=1991 |publisher=Van Nostrand Reinhold |last=Davis |first=Lawrence |isbn=0-442-00173-8 |location=New York |oclc=23081440}}</ref><ref name=":1">{{Cite book |last1=Eiben |first1=A.E. |url=http://link.springer.com/10.1007/978-3-662-44874-8 |title=Introduction to Evolutionary Computing |last2=Smith |first2=J.E. |date=2015 |publisher=Springer |isbn=978-3-662-44873-1 |edition=2nd |series=Natural Computing Series |location=Berlin, Heidelberg |pages=49–78 |language=en |chapter=Representation, Mutation, and Recombination |doi=10.1007/978-3-662-44874-8 |s2cid=20912932}}</ref><ref>{{Cite book |last1=Yu |first1=Xinjie |url=https://www.worldcat.org/oclc/654380156 |title=Introduction to evolutionary algorithms |last2=Gen |first2=Mitsuo |date=2010 |publisher=Springer |isbn=978-1-84996-129-5 |series=Decision Engineering |location=London |pages=40–63 |language=en |chapter=Encoding and Operators |doi=10.1007/978-1-84996-129-5 |oclc=654380156}}</ref><ref>{{Cite book |last1=Yu |first1=Xinjie |url=http://link.springer.com/10.1007/978-1-84996-129-5 |title=Introduction to Evolutionary Algorithms |last2=Gen |first2=Mitsuo |date=2010 |publisher=Springer |isbn=978-1-84996-128-8 |series=Decision Engineering |volume= |location=London |pages=285–299 |chapter=Variation Operators for Permutation Code |doi=10.1007/978-1-84996-129-5}}</ref><ref name=":5">{{Cite book |last1=Booker |first1=Lashon B. |url=https://www.worldcat.org/oclc/45730387 |title=Evolutionary computation. Vol. 1, Basic algorithms and operators |last2=Fogel |first2=David B. |last3=Whitley |first3=Darrell |last4=Angeline |first4=Peter J. |last5=Eiben |first5=A.E. |date=2000 |publisher=Institute of Physics Pub |isbn=0-585-30560-9 |editor-last=Bäck |editor-first=Thomas |location=Bristol |pages=256–307 |language=en |chapter=Recombination |oclc=45730387 |editor-last2=Fogel |editor-first2=David B. |editor-last3=Michalewicz |editor-first3=Zbigniew}}</ref>