Editing Genetic algorithm (section)

== History ==
In 1950, [[Alan Turing]] proposed a "learning machine" which would parallel the principles of evolution.<ref name="mind.oxfordjournals.org">{{cite journal|last1=Turing|first1=Alan M.|title=Computing machinery and intelligence|journal=Mind|volume=LIX|issue=238|pages=433–460|doi=10.1093/mind/LIX.236.433|date=October 1950}}</ref> Computer simulation of evolution started as early as in 1954 with the work of [[Nils Aall Barricelli]], who was using the computer at the [[Institute for Advanced Study]] in [[Princeton, New Jersey]].<ref name="Barricelli 1954 45–68">{{cite journal|last=Barricelli|first=Nils Aall|year=1954|author-link=Nils Aall Barricelli|title=Esempi numerici di processi di evoluzione|journal=Methodos|pages=45–68}}</ref><ref name="Barricelli 1957 143–182">{{cite journal|last=Barricelli|first=Nils Aall|year=1957|author-link=Nils Aall Barricelli|title=Symbiogenetic evolution processes realized by artificial methods|journal=Methodos|pages=143–182}}</ref> His 1954 publication was not widely noticed. Starting in 1957,<ref name="Fraser 1957 484–491">{{cite journal|last=Fraser|first=Alex|author-link=Alex Fraser (scientist)|year=1957|title=Simulation of genetic systems by automatic digital computers. I. Introduction|journal=Aust. J. Biol. Sci.|volume=10|issue=4|pages=484–491|doi=10.1071/BI9570484|doi-access=free}}</ref> the Australian quantitative geneticist [[Alex Fraser (scientist)|Alex Fraser]] published a series of papers on simulation of [[artificial selection]] of organisms with multiple loci controlling a measurable trait. From these beginnings, computer simulation of evolution by biologists became more common in the early 1960s, and the methods were described in books by Fraser and Burnell (1970)<ref name="Fraser 1970">{{cite book|last1=Fraser|first1=Alex|author-link=Alex Fraser (scientist)|first2=Donald |last2=Burnell|year=1970|title=Computer Models in Genetics|publisher=McGraw-Hill|location=New York|isbn=978-0-07-021904-5}}</ref> and Crosby (1973).<ref name="Crosby 1973">{{cite book|last=Crosby|first=Jack L.|year=1973|title=Computer Simulation in Genetics|publisher=John Wiley & Sons|location=London|isbn=978-0-471-18880-3}}</ref> Fraser's simulations included all of the essential elements of modern genetic algorithms. In addition, [[Hans-Joachim Bremermann]] published a series of papers in the 1960s that also adopted a population of solution to optimization problems, undergoing recombination, mutation, and selection. Bremermann's research also included the elements of modern genetic algorithms.<ref>[http://berkeley.edu/news/media/releases/96legacy/releases.96/14319.html 02.27.96 - UC Berkeley's Hans Bremermann, professor emeritus and pioneer in mathematical biology, has died at 69]</ref> Other noteworthy early pioneers include Richard Friedberg, George Friedman, and Michael Conrad. Many early papers are reprinted by [[David B. Fogel|Fogel]] (1998).<ref>{{cite book|editor-last=Fogel|editor-first=David B. |year=1998|title=Evolutionary Computation: The Fossil Record|publisher=IEEE Press|location=New York|isbn=978-0-7803-3481-6}}</ref>

Although Barricelli, in work he reported in 1963, had simulated the evolution of ability to play a simple game,<ref>{{cite journal|last=Barricelli|first=Nils Aall|year=1963|title=Numerical testing of evolution theories. Part II. Preliminary tests of performance, symbiogenesis and terrestrial life|journal=Acta Biotheoretica|volume=16|issue=3–4|pages=99–126|doi=10.1007/BF01556602|s2cid=86717105}}</ref> [[artificial evolution]] only became a widely recognized optimization method as a result of the work of [[Ingo Rechenberg]] and [[Hans-Paul Schwefel]] in the 1960s and early 1970s &ndash; Rechenberg's group was able to solve complex engineering problems through [[Evolution strategy|evolution strategies]].<ref>{{cite book|last=Rechenberg|first=Ingo|year=1973|title=Evolutionsstrategie|place=Stuttgart|publisher=Holzmann-Froboog|isbn=978-3-7728-0373-4}}</ref><ref>{{cite book|last=Schwefel|first=Hans-Paul|year=1974|title=Numerische Optimierung von Computer-Modellen (PhD thesis)}}</ref><ref>{{cite book|last=Schwefel|first=Hans-Paul|year=1977|title=Numerische Optimierung von Computor-Modellen mittels der Evolutionsstrategie : mit einer vergleichenden Einführung in die Hill-Climbing- und Zufallsstrategie|place=Basel; Stuttgart | publisher=Birkhäuser| isbn=978-3-7643-0876-6}}</ref><ref>{{cite book|last=Schwefel|first=Hans-Paul|year=1981|title=Numerical optimization of computer models (Translation of 1977 Numerische Optimierung von Computor-Modellen mittels der Evolutionsstrategie|place=Chichester; New York|publisher=Wiley|isbn=978-0-471-09988-8}}</ref> Another approach was the evolutionary programming technique of [[Lawrence J. Fogel]], which was proposed for generating artificial intelligence. [[Evolutionary programming]] originally used finite state machines for predicting environments, and used variation and selection to optimize the predictive logics. Genetic algorithms in particular became popular through the work of [[John Henry Holland|John Holland]] in the early 1970s, and particularly his book ''Adaptation in Natural and Artificial Systems'' (1975). His work originated with studies of [[cellular automata]], conducted by [[John Henry Holland|Holland]] and his students at the [[University of Michigan]]. Holland introduced a formalized framework for predicting the quality of the next generation, known as [[Holland's Schema Theorem]]. Research in GAs remained largely theoretical until the mid-1980s, when The First International Conference on Genetic Algorithms was held in [[Pittsburgh, Pennsylvania]].

===Commercial products===
In the late 1980s, General Electric started selling the world's first genetic algorithm product, a mainframe-based toolkit designed for industrial processes.<ref>{{Cite book|url=https://books.google.com/books?id=-MszVdu_PAMC&q=general+electric+genetic+algorithm+mainframe|title=An Approach to Designing an Unmanned Helicopter Autopilot Using Genetic Algorithms and Simulated Annealing|last=Aldawoodi|first=Namir|year=2008|isbn=978-0549773498|pages=99|via=Google Books}}</ref>{{Circular reference|date=January 2021}} 
In 1989, Axcelis, Inc. released [[Evolver (software)|Evolver]], the world's first commercial GA product for desktop computers. [[The New York Times]] technology writer [[John Markoff]] wrote<ref>{{cite news|last=Markoff|first=John|title=What's the Best Answer? It's Survival of the Fittest|newspaper=New York Times|url=https://www.nytimes.com/1990/08/29/business/business-technology-what-s-the-best-answer-it-s-survival-of-the-fittest.html|access-date=2016-07-13|date=29 August 1990}}</ref> about Evolver in 1990, and it remained the only interactive commercial genetic algorithm until 1995.<ref>Ruggiero, Murray A.. (1 August 2009) [http://www.futuresmag.com/2009/08/01/fifteen-years-and-counting?t=technology&page=2 Fifteen years and counting] {{Webarchive|url=https://web.archive.org/web/20160130054823/http://www.futuresmag.com/2009/08/01/fifteen-years-and-counting?t=technology&page=2 |date=30 January 2016 }}. Futuresmag.com. Retrieved on 2013-08-07.</ref> Evolver was sold to Palisade in 1997, translated into several languages, and is currently in its 6th version.<ref>[http://www.palisade.com/evolver/ Evolver: Sophisticated Optimization for Spreadsheets]. Palisade. Retrieved on 2013-08-07.</ref> Since the 1990s, [[MATLAB]] has built in three [[derivative-free optimization]] heuristic algorithms (simulated annealing, particle swarm optimization, genetic algorithm) and two direct search algorithms (simplex search, pattern search).<ref>{{cite journal | doi=10.1109/ACCESS.2019.2923092 | title=Benchmarks for Evaluating Optimization Algorithms and Benchmarking MATLAB Derivative-Free Optimizers for Practitioners' Rapid Access | year=2019 | last1=Li | first1=Lin | last2=Saldivar | first2=Alfredo Alan Flores | last3=Bai | first3=Yun | last4=Chen | first4=Yi | last5=Liu | first5=Qunfeng | last6=Li | first6=Yun | journal=IEEE Access | volume=7 | pages=79657–79670 | s2cid=195774435 | doi-access=free | bibcode=2019IEEEA...779657L }}</ref>