简介：Thispaperstudiesatwostagesupplychainwithadominantupstreampartner.ManufactureristhedominantpartnerandoperatesinaJust-in-Timeenvironment.Productionisdoneinasinglemanufacturinglinecapableofproducingtwoproductswithoutstoppingtheproductionforswitchingfromoneproducttotheother.Themanufacturerimposesconstraintsonthedistributorbyadheringtohisfavorableproductionschedulewhichminimizeshismanufacturingcost.Distributorontheotherhandcaterstoretailers'orderswithoutincurringanyshortagesandisresponsibleformanagingtheinventoryoffinishedgoods.Adheringtomanufacturer'sschedulemayleadtohighinventorycarryingcostsforthedistributor.Distributor'sproblem,whichistofindanoptimaldistributionsequencewhichminimizesthedistributor'sinventorycostundertheconstraintimposedbythemanufacturerisprovedNP-HardbyManojetal.(2008).Therefore,solvinglargesizeproblemsrequireefficientheuristics.Wedevelopalgorithmsforthedistributionproblembyexploitingitsstructuralproperties.Weproposetwoheuristicsandusetheirsolutionsintheinitialpopulationofageneticalgorithmtoarriveatsolutionswithanaveragedeviationoflessthan3.5%fromtheoptimalsolutionforpracticalsizeproblems.

简介：1.IntroductionGopalsamyandLadajs[1]illtroducedthefollowingdelayLotka-Volterratypesinglespeciespopulationgrowthmodel:wherea,b,ctTarerealconstants,anda>0,c>0,T20.Ifa>0,b<0andc=0,then(1.1)reducestotheLogisticequation.Ifb>0,(l.1)exhibitstheso--calledAlic...

简介：作为绝对错误方法的一种选择，例如最不方形、最少的绝对偏差评价，一个产品亲戚错误评价为一个趋于增加的单个索引回归模型被建议。在模型的回归系数经由一个二阶段的过程被估计，他们象一致性和规度那样的统计性质被学习。包括模拟和一个身体脂肪例子的数字研究证明建议方法表现很好。

简介：Weconsideramanpowerplanningproblemwithsingleemployeetypeoveralongplanninghorizonandanalyzetheoptimalrecruitmentanddismissalpolices.Dynamicdemandsformanpowermustbefulfilledbyallocatingenoughnumberofemployees.Costsforeveryemployeeincludesalary,recruitmentanddismissalcosts,inparticular,setupcostswhenrecruitment/dismissalactivitiesoccur.Weformulatetheproblemasamulti-perioddecisionmodel.Thenweanalyzepropertiesoftheproblemandgiveanimproveddynamicprogrammingalgorithmtominimizethetotalcostovertheentireplanninghorizon.Wereportcomputationalresultstoillustratetheeffectivenessoftheapproach.

简介：InthispaperweprovethatthesinglemachinecommonduedateweightedtardinessproblemisNP-hard.

简介：Thispaperproposesasufficientcondition,ifthepropertiesofthebilevelprogrammingsatisfiedthecondition,wecansolvethebilevelprogrammingbysolvingsinglelevelprogramming.Itbecomeseasyandsimpletosolvethebilevelprogramming.

简介：以便折衷探索/利用并且由房间geneticalgorithm启发了一个房间移动转线路操作员因为进化算法(EA)在这个paper.The定义领域被建议被划分成重新尺寸立方的子域(房间)和在一个n维的立方体的每individuallocates。如果他们在不同房间(探索)并且随后，thecrossover的房间数字配对的房间移动转线路第一交换从它的起始的地方转移firstindividual到另外的个人“s房间地方。如果他们已经在thesame房间，启发式的转线路(利用)被使用。有基因差异的vary的Cell-shift/heuristic转线路adaptivelyexecutes探索/利用搜索。当与最近的著名FEP进化算法作比较时，房间移动EAhasexcellent表演通常以十上的效率和功效使用了optimizationbenchmarks。

简介：Wediscussasingle-periodinventorysystemwithageneralS-shapedutilityfunctionandexponentialdemand.Itisshownthatthereexistsastate-dependentorder-up-topolicytobeoptimal.Behaviorsofoptimalpolicyareillustratedbyanumericalexample.

简介：Thispaperproposesagroupdecisionmakingmethodbasedonentropyofneutrosophiclinguisticsetsandgeneralizedsinglevaluedneutrosophiclinguisticoperators.Thismethodisappliedtosolvethemultipleattributegroupdecisionmakingproblemsundersinglevaluedneutrosophicliguisticenvironment,inwhichtheattributeweightsarecompletelyunknown.First,theattributeweightsareobtainedbyusingtheentropyofneutrosophiclinguisticsets.Thenthreegeneralizedsinglevaluedneutrosophiclinguisticoperatorsareintroduced,includingthegeneralizedsinglevaluedneutrosophiclinguisticweightedaveraging(GSVNLWA)operator,thegeneralizedsinglevaluedneutrosophiclinguisticorderedweightedaveraging(GSVNLOWA)operatorandthegeneralizedsinglevaluedneutrosophiclinguistichybridaveraging(GSVNLHA)operator,andtheGSVNLWAandGSVNLHAoperatorsareusedtoaggregateinformation.Furthermore,similaritymeasurebasedonsinglevaluedneutrosophiclinguisticnumbersisdefinedandusedtosortthealternativesandobtainthebestalternative.Finally,anillustrativeexampleisgiventodemonstratethefeasibilityandeffectivenessofthedevelopedmethod.

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