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1、ARTICLEINPRESSEngineeringApplicationsofArtificialIntelligence23(2010)772–779ContentslistsavailableatScienceDirectEngineeringApplicationsofArtificialIntelligencejournalhomepage:www.elsevier.com/locate/engappaiAnadaptiveoptimizationtechniquefordynamicenvironm
2、entsa,bLiLiu,S.RanjiRanjithanaSchoolofCivilEngineering,HefeiUniversityofTechnology,230009Hefei,Anhui,ChinabDepartmentofCivil,Construction,andEnvironmentalEngineering,NorthCarolinaStateUniversity,27695Raleigh,NorthCarolina,USAarticleinfoabstractArticlehis
3、tory:Theuseofevolutionaryalgorithms(EAs)isbeneficialforaddressingoptimizationproblemsindynamicReceived17May2009environments.Theobjectivefunctionforsuchproblemschangescontinually;thus,theoptimalReceivedinrevisedformsolutionslikewisechange.Suchdynamicchanges
4、posechallengestoEAsduetothepooradaptabilityof9November2009EAsoncetheyhaveconverged.However,appropriatepreservationofasufficientlevelofindividualAccepted16January2010diversitymayhelptoincreasetheadaptivesearchcapabilityofEAs.ThispaperproposesanEA-basedAvail
5、ableonline18February2010AdaptiveDynamicOPtimizationTechnique(ADOPT)forsolvingtime-dependentoptimizationKeywords:problems.ThepurposeofthisapproachistoidentifythecurrentoptimalsolutionaswellasasetofEvolutionaryalgorithmsalternativesthatisnotonlywidespreadin
6、thedecisionspace,butalsoperformswellwithrespecttotheAdaptivedynamicoptimizationobjectivefunction.TheresultantsolutionsmaythenserveasabasissolutionforthesubsequentsearchDiversitywhilechangeisoccurring.Thus,suchanalgorithmavoidstheclusteringofindividualsint
7、hesameAdaptabilityregionaswellasadaptstochangingenvironmentsbyexploitingdiversepromisingregionsintheContaminantsourceidentificationsolutionspace.Applicationofthealgorithmtoatestproblemandagroundwatercontaminantsourceidentificationproblemdemonstratestheeffec
8、tivenessofADOPTtoadaptivelyidentifysolutionsindynamicenvironments.&2010ElsevierLtd.Allrightsreserved.1.Introductionment,limitingtheapplicationoftraditionalEAstosolvedynamicoptimizationproblems.Nevertheless,variousme
