MERGING OPTIMALITY CONDITIONS WITH GENETIC ALGORITHM OPERATORS TO SOLVE SINGLE MACHINE TOTAL WEIGHTED TARDINESS PROBLEM-中国Betway体育网页登陆

摘要 Inthispaper,aconstrainedgeneticalgorithm(CGA)isproposedtosolvethesinglemachinetotalweightedtardinessproblem.TheproposedCGAincorporatesdominancerulesfortheproblemunderconsiderationintotheGAoperators.ThisincorporationshouldenabletheproposedCGAtoobtainclosetooptimalsolutionswithmuchlessdeviationandmuchlesscomputationaleffortthantheconventionalGA(UGA).SeveralexperimentswereperformedtocomparethequalityofsolutionsobtainedbythethreeversionsofboththeCGAandtheUGAwiththeresultsobtainedbyadynamicprogrammingapproach.ThecomputationalresultsshowedthattheCGAwasbetterthantheUGAinbothqualityofsolutionsobtainedandtheCPUtimeneededtoobtaintheclosetooptimalsolutions.ThethreeversionsoftheCGAreducedthepercentagedeviationby15.6%,61.95%,and25%respectivelyandobtainedclosetooptimalsolutionswith59%lowerCPUtimethanwhatthethreeversionsoftheUGAdemanded.TheCGAperformedbetterthantheUGAintermsofqualityofsolutionsandcomputationaleffortwhenthepopulationsizeandthenumberofgenerationsaresmaller.

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MERGING OPTIMALITY CONDITIONS WITH GENETIC ALGORITHM OPERATORS TO SOLVE SINGLE MACHINE TOTAL WEIGHTED TARDINESS PROBLEM

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