Editing Tournament selection (section)

== Advantages ==
In comparison with the (stochastic) [[fitness proportionate selection]] method, tournament selection is often implemented in practice due to its lack of stochastic noise.<ref>{{cite journal|last1=Blickle|first1=Tobias|last2=Thiele|first2=Lothar|title=A Comparison of Selection Schemes Used in Evolutionary Algorithms|journal=Evolutionary Computation|date=December 1996|volume=4|issue=4|pages=361–394|doi=10.1162/evco.1996.4.4.361|citeseerx=10.1.1.15.9584|s2cid=42718510}}</ref>

Tournament selection has several benefits over alternative selection methods for genetic algorithms (for example, [[fitness proportionate selection]] and [[reward-based selection]]): it is efficient to code, works on parallel architectures and allows the selection pressure to be easily adjusted.<ref name=miller-goldberg />  Tournament selection has also been shown to be independent of the scaling of the genetic algorithm [[fitness function]] (or '[[Loss function|objective function]]') in some classifier systems.<ref>{{cite book |editor-last1=Cantú-Paz |editor-first1=Erick |title=Genetic and Evolutionary Computation -- GECCO 2003 : Genetic and Evolutionary Computation Conference Chicago, IL, USA, July 12-16, 2003 Proceedings, Part II |date=2003 |publisher=Springer-Verlag Berlin Heidelberg |location=Berlin, Heidelberg |isbn=978-3-540-45110-5}}</ref><ref>{{cite journal|last1=Goldberg|first1=David|last2=Deb|first2=Kalyanmoy|title=A comparative analysis of selection schemes used in genetic algorithms|journal=Foundations of Genetic Algorithms|date=1991|volume=1|pages=69–93|doi=10.1016/b978-0-08-050684-5.50008-2|isbn=9780080506845|s2cid=938257|url=https://pdfs.semanticscholar.org/feee/c4229f71c6ed155e2f2b732464dbc8c5b93c.pdf|archive-url=https://web.archive.org/web/20180717131907/https://pdfs.semanticscholar.org/feee/c4229f71c6ed155e2f2b732464dbc8c5b93c.pdf|url-status=dead|archive-date=2018-07-17}}</ref>