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ID:34578355
大小:264.73 KB
页数:25页
时间:2019-03-08
《embedding branch and bound within evolutionary algorithms》由会员上传分享,免费在线阅读,更多相关内容在教育资源-天天文库。
1、EmbeddingBranchandBoundwithinEvolutionaryAlgorithmsCarlosCottaandJos¶eM.TroyaDept.LenguajesyCienciasdelaComputaci¶on,UniversityofM¶alagaETSIInform¶atica(3.2.49),CampusdeTeatinos,29071-M¶alaga,SPAINccottap@lcc.uma.esAbstractAframeworkforhybridizingevolutionaryalgori
2、thmswiththebranch-and-boundalgorithm(B&B)ispresentedinthispaper.ThisframeworkisbasedonusingB&Basanoperatorembeddedintheevolutionaryalgorithm.Theresultinghybridoperatorwillintelligentlyexplorethedynasticpotential(possiblechildren)ofthesolutionsbeingrecombined,provid
3、ingthebestcombinationofformae(generalizedschemata)thatcanbeconstructedwithoutintroducingimplicitmutation.Asabasisforstudyingthisoperator,thegeneralfunctioningoftransmittingrecombinationisconsidered.Twoimportantconceptsareintroduced,compatibilitysets,andgranularityo
4、ftherepresentation.Theseconceptsarestudiedinthecontextofdi®erentkindsofrepresentation:orthogonal,non-orthogonalseparable,andnon-separable.Theresultsofanextensiveexperimentalevaluationarereported.Itisshownthatthismodelcanbeusefulwhenproblemknowledgeisavailableinthef
5、ormofanoptimisticevaluationfunction.Scalabilityissuesarealsoconsidered.Acontrolmechanismisproposedtoalleviatetheincreasingcomputationalcostofthealgorithmforhighlymultidimensionalproblems.1IntroductionEvolutionaryAlgorithms[1]arepowerfulheuristicsforoptimizationbase
6、dontheprinciplesofnaturalevolution,namelyadaptationandsurvivalofthe¯ttest.Thesetechniquesarebasedontheiterativegenerationoftentativesolutionsforatargetproblem:startingfromapopulation(pool)ofrandomlycreatedindividuals(solutions),abasiccyclecomprisingselection(promis
7、ingsolutionsarepickedfromthepool),reproduction(newsolutionsarecreatedbymodifyingselectedsolutions),andreplacement(thepoolisupdatedbyreplacingsomeexistingsolutionsbythenewlycreatedones)isperformed.A¯tnessfunctionmeasuringthegoodnessofsolutionsisusedtodrivethewholepr
8、ocess,especiallydur-ingtheselectionstage.Evolutionarycomputationconstitutesnowadaysastate-of-the-artapproachtotacklehardoptimizationproblemsforwh
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