Editing Genetic operator (section)

===Selection===
{{main|Selection (evolutionary algorithm)}}
Selection operators give preference to better candidate solutions (chromosomes), allowing them to pass on their 'genes' to the next generation ([[iteration]]) of the algorithm. The best solutions are determined using some form of [[objective function]] (also known as a '[[fitness function]]' in evolutionary algorithms), before being passed to the crossover operator. Different methods for choosing the best solutions exist, for example, [[fitness proportionate selection]] and [[tournament selection]].<ref>{{Cite book |last1=Eiben |first1=A.E. |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=80–87 |language=en |chapter=Parent Selection |doi=10.1007/978-3-662-44874-8}}</ref> A further or the same selection operator is used to determine the individuals for being selected to form the next parental generation. The selection operator may also ensure that the best solution(s) from the current generation always become(s) a member of the next generation without being altered;<ref>{{Cite book |last1=Eiben |first1=A.E. |url=https://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=87–90 |language=en |chapter=Survivor Selection |doi=10.1007/978-3-662-44874-8}}</ref> this is known as ''elitism'' or ''elitist selection''.<ref name=ga-intro /><ref name=ga-intro2>{{cite web|title=Introduction to Genetic Algorithm|url=http://www.rennard.org/alife/english/gavintrgb.html|accessdate=20 August 2015}}</ref><ref>{{Cite book |last1=Eiben |first1=A.E. |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=89 |language=en |doi=10.1007/978-3-662-44874-8}}</ref>