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1、ComputersinHumanBehavior27(2011)1482–1492ContentslistsavailableatScienceDirectComputersinHumanBehaviorjournalhomepage:www.elsevier.com/locate/comphumbehInteractivegeneticalgorithmswithindividual’sfuzzy?tnessDun-weiGong?,JieYuan,Xiao-yanSunSchoolofInformationandElectricalEngineering,ChinaUniv
2、ersityofMiningandTechnology,Xuzhou,ChinaarticleinfoabstractArticlehistory:InteractivegeneticalgorithmsareeffectivemethodstosolveanoptimizationproblemwithimplicitorAvailableonline30October2010fuzzyindices,andhavebeensuccessfullyappliedtomanyreal-worldoptimizationproblemsinrecentyears.Intradit
3、ionalinteractivegeneticalgorithms,manyresearchersadoptanaccuratenumbertoKeywords:expressanindividual’s?tnessassignedbyauser.Butitisdif?cultforthisexpressiontoreasonablyre?ectOptimizationauser’sfuzzyandgradualcognitivetoanindividual.WepresentaninteractivegeneticalgorithmwithanGeneticalgorithm
4、sindividual’sfuzzy?tnessinthispaper.Firstly,weadoptafuzzynumberdescribedwithaGaussianmem-Individual’s?tnessbershipfunctiontoexpressanindividual’s?tness.Then,inordertocomparedifferentindividuals,weFuzzynumbergeneratea?tnessintervalbasedona-cutset,andobtaintheprobabilityofindividualdominanceby
5、Fashiondesignuseoftheprobabilityofintervaldominance.Finally,wedeterminethesuperiorindividualintournamentselectionwithsizetwobasedontheprobabilityofindividualdominance,andperformthesubsequentevolutions.Weapplytheproposedalgorithmtoafashionevolutionarydesignsystem,atypicaloptimi-zationproblemw
6、ithanimplicitindex,andcompareitwithtwointeractivegeneticalgorithms,i.e.,aninteractivegeneticalgorithmwithanindividual’saccurate?tnessandaninteractivegeneticalgorithmwithanindividual’sinterval?tness.Theexperimentalresultsshowthattheproposedalgorithmisadvan-tageousinalleviatinguserfatigueandlo
7、okingforuser’ssatisfactoryindividuals.ó2010ElsevierLtd.Allrightsreserved.1.Introduction?tnessaremorelikelytobeselectedtogenerateindividualsinthenextgeneration.AnewgenerationofindividualsisgeneratedOptimizationproblemsareverycommoninreal-worldapplic
