简介：Thispaperproposesanautomaticmethodofporecombinationrecognition,whichisanimportantfeaturetohardwoodrecognition.Afterextractingedgefromwoodmicroscopiccross-section,basedonareahistogramofthesimilarcircleregions,themethodclassifiesallregionsintotwoclasseswithmaximumbetween-classvariance,soastodistinguishtheporefromothertextures,whicharesimilarinshapesbutdifferentinsizes.Meanwhile,secondobjectivefunctionaboutaverageareaofclosedregionsisusedtoimprovetheporesegmentationperformance.Atlast,themethodusesadjacencydegreeofporesettojudgeporecombination.Theexperimentsdemonstratethatthetaskofporesegmentationcanbecompletedsuccessfullyforallkindsofporedistributionandcombination,andalsothecorrectcombinationsofporesaregiven.

简介：在这份报纸，我们考虑解决多客观的编程问题的中心的一个方法，在包含的客观函数是凹面函数，可行的点的集合是凸的的地方。算法被定义以便必须在它的实行期间被解决的亚问题可以被有限步的过程解决。条件在算法更多样地在哪个下面产生可行的点和限制的序列下面被给有累积点的向量令人满意KKT条件。最后，我们为解决多客观的编程问题建立中心算法的建议方法的集中。

简介：

简介：

简介：这篇论文基于多客观的最佳的控制系统建议非线性的控制器和一个大阶段角度津贴设计方法的一种新类型。与建议方法，系统的性能变得比原来的系统的好。然后，雷达伺服系统的一个例子与大阶段角度津贴被设计多客观的最佳的设计方法。最后，性能基于计算机模拟证明多客观的最佳的系统比线性最佳的系统优异。

简介：Amulti-objectivehybridgeneticbasedoptimizationalgorithmisproposedaccordingtothemulti-objectivePropertyofinverseplanning.Itisbasedonhybridadaptivegeneticalgorithmwhichcombinesthesimulatedannealing,usesadaptivecrossoverandmutation,andadoptsnichedtournamentselection.Theresultoftheteatcalculatationdemonstratesthatanexcellentconvergingspeedcanbeachievedusingthisapproach.

简介：

简介：Withthecontinuousimprovementofthetrainspeed,thedynamicenvironmentoftrainsturnsouttobeaerodynamicdomination.Solvingtheaerodynamicproblemshasbecomeoneofthekeyfactorsofthehigh-speedtrainheaddesign.Giventhattheaerodynamicdragisasignificantfactorthatrestrainstrainspeedandenergyconservation,reducingtheaerodynamicdragisthusanimportantconsiderationofthehigh-speedtrainheaddesign.However,thereductionoftheaerodynamicdragmayincreaseotheraerodynamicforces(moments),possiblydeterioratingtheoperationalsafetyofthetrain.Themulti-objectiveoptimizationdesignmethodofthehigh-speedtrainheadwasproposedinthispaper,andtheaerodynamicdragandloadreductionfactorweresettobeoptimizationobjectives.Theautomaticmulti-objectiveoptimizationdesignofthehigh-speedtrainheadcanbeachievedbyintegratingaseriesofproceduresintothemulti-objectiveoptimizationalgorithm,suchastheestablishmentof3Dparametricmodel,theaerodynamicmeshgeneration,thecalculationoftheflowfieldaroundthetrain,andthevehiclesystemdynamics.Thecorrelationbetweentheoptimizationobjectivesandoptimizationvariableswasanalyzedtoobtainthemostimportantoptimizationvariables,andafurtheranalysisofthenonlinearrelationshipbetweenthekeyoptimizationvariablesandtheoptimizationobjectiveswasobtained.Afteroptimization,theaerodynamicdragofoptimizedtrainwasreducedbyupto4.15%,andtheloadreductionfactorwasreducedbyupto1.72%.

简介：城市的总线网络的多客观的优化能帮助改进运输系统的操作效率并且为在中国减少城市的交通拥挤开发策略。工作使用了累积前景理论，当前为在无常下面的决定的最有影响的模型，优化城市的公共汽车网络。完成研究目的，工作开发了城市的总线网络优化，包括的优化原则，优化目的和限制的理论框架。而且，优化目的能包括地从时间，空间和价值的尺寸反映旅客和总线公司的期望。它在以前的研究独自与仅仅一个股东或尺寸相比更科学、合理。另外，为由到理想的答案TOPSIS的类似的顺序偏爱的技术被用来决定积极、否定的理想的选择。在优化选择和理想的选择之间的关联被灰关系分析同时估计。累积前景理论CPT被用来由比较每种选择的全面前景价值决定最好的选择，精确地在实际生活与期望的用途理论相比描述决策行为。最后，Xian的大小写证明方法能更好调整总线网络，并且优化解决方案是更合理的满足实际需要。

简介：Thispaperproposestheconceptsofgeneralizedαk-majorefficientsolutionsandgeneralizedαkmajoroptimalsolutionsformulti-objectiveprogramming,andstudiestheirsomeimportantproperties.

简介：Amulti-objectiveoptimizationofnon-uniformbeamsispresentedforminimumradiatedsoundpowerandweight.Thetransfermatrixmethodisusedtocomputethestructuralandacousticresponsesofanon-uniformbeamaccuratelyandefficiently.Themulti-objectiveparticleswarmoptimizationtechniqueisappliedtosearchtheParetooptimalsolutionsthatrepresentvariouscompromisesbetweenweightandsoundradiation.Severalconstraintsareimposed,whichsubstantiallyreducethevolumefractionoffeasiblesolutionsinthedesignspace.Twononuniformbeamswithdifferentboundaryconditionsarestudiedtodemonstratethemulti-objectiveoptimaldesignsofthestructure.

简介：Asanimportantelementinsustainablebuildingdesign,thebuildingenvelopehasbeenwitnessingaconstantshiftinthedesignapproach.Integratingmulti-objectiveoptimization(MOO)intothebuildingenvelopedesignprocessisverypromising,butnoteasytorealizeinanactualprojectduetoseveralfactors,includingthecomplexityofoptimizationmodelconstruction,lackofadynamic-visualizationcapacityinthesimulationtoolsandconsiderationofhowtomatchtheoptimizationwiththeactualdesignprocess.Toovercomethesedifficulties,thisstudyconstructedanintegratedbuildingenvelopedesignprocess(IBEDP)basedonparametricmodelling,whichwasimplementedusingGrasshopperplatformandinterfacestocontrolthesimulationsoftwareandoptimizationalgorithm.ArailwaystationwasselectedasacasestudyforapplyingtheproposedIBEDP,whichalsoutilizedagrid-basedvariabledesignapproachtoachieveflexibleoptimumfenestrations.Tofacilitatethestepwisedesignprocess,anovelstrategywasproposedwithatwo-stepoptimization,whichoptimizedvariouscategoriesofvariablesseparately.Comparedwithaone-stepoptimization,thoughtheproposedstrategyperformedpoorlyinthediversityofsolutions,thequantitativeassessmentofthequalitiesofPareto-optimumsolutionsetsillustratesthatitissuperior.

简介：Afuzzyparticleswarmoptimization(PSO)onthebasisofelitearchivingisproposedforsolvingmulti-objectiveoptimizationproblems.First,anewperturbationoperatorisdesigned,andtheconceptsoffuzzyglobalbestandfuzzypersonalbestaregivenonbasisofthenewoperator.Afterthat,particleupdatingequationsarerevisedonthebasisofthetwonewconceptstodiscouragetheprematureconvergenceandenlargethepotentialsearchspace;second,theelitearchivingtechniqueisusedduringtheprocessofevolution,namely,theeliteparticlesareintroducedintotheswarm,whereastheinferiorparticlesaredeleted.Therefore,thequalityoftheswarmisensured.Finally,theconvergenceofthisswarmisproved.TheexperimentalresultsshowthatthenondominatedsolutionsfoundbytheproposedalgorithmareuniformlydistributedandwidelyspreadalongtheParetofront.

简介：Inthispaper,amulti-objectiveparticleswarmoptimization(MOPSO)algorithmandanondominatedsortinggeneticalgorithmⅡ(NSGA-Ⅱ)areusedtooptimizetheoperatingparametersofa1.6L,sparkignition(SI)gasolineengine.Theaimofthisoptimizationistoreduceengineemissionsintermsofcarbonmonoxide(CO),hydrocarbons(HC),andnitrogenoxides(NOx),whicharethecausesofdiverseenvironmentalproblemssuchasairpollutionandglobalwarming.Stationaryenginetestswereperformedfordatageneration,covering60operatingconditions.Artificialneuralnetworks(ANNs)wereusedtopredictexhaustemissions,whoseinputswerefromsixengineoperatingparameters,andtheoutputswerethreeresultingexhaustemissions.TheoutputsofANNswereusedtoevaluateobjectivefunctionswithintheoptimizationalgorithms:NSGA-ⅡandMOPSO.Thenadecision-makingprocesswasconducted,usingafuzzymethodtoselectaParetosolutionwithwhichthebestemissionreductionscanbeachieved.TheNSGA-Ⅱalgorithmachievedreductionsofatleast9.84%,82.44%,and13.78%forCO,HC,andNOx,respectively.WithaMOPSOalgorithmthereachedreductionswereatleast13.68%,83.80%,and7.67%forCO,HC,andNOx,respectively.

简介：

简介：Avague-set-basedfuzzymulti-objectivedecisionmakingmodelisdevelopedforevaluatingbiddingplansinabid-dingpurchaseprocess.Agroupofdecision-makers(DMs)firstindependentlyassessbiddingplansaccordingtotheirexperienceandpreferences,andtheseassessmentsmaybeexpressedaslinguisticterms,whicharethenconvertedtofuzzynumbers.Theresultingdecisionmatricesarethentransformedtoobjectivemembershipgradematrices.Thelowerboundofsatisfactionandupperboundofdissatisfactionareusedtodetermineeachbiddingplan’ssupporting,opposing,andneutralobjectivesets,whichtogetherdeterminethevaguevalueofabiddingplan.Finally,ascorefunctionisemployedtorankallbiddingplans.Anewscorefunctionbasedonvaguesetsisintroducedinthemodelandanovelmethodispresentedforcalculatingthelowerboundofsat-isfactionandupperboundofdissatisfaction.Inavague-set-basedfuzzymulti-objectivedecisionmakingmodel,differentvalua-tionsforupperandlowerboundsofsatisfactionusuallyleadtodistinctrankingresults.Therefore,itiscrucialtoeffectivelycontainDMs’arbitrarinessandsubjectivitywhenthesevaluesaredetermined.

简介：

简介：

简介：Amulti-objectiveoptimizationapproachfortherollshiftingstrategyincrossrollingcampaignsofhotstripmillsispresented.Theeffectofdifferentrollshiftingstrategiesonrollwearcontourisstudiedbynumericalsimulation,andtwoevaluationindexes,namelybodysmoothnessandedgesmoothness,areproposed.Theaveragebodysmoothnessandaveragerollingedgesmoothnessofallstripsinarollingcampaignaretakenastheobjectivefunctions,theshiftingpositionsofallwidestripsasthedecisionvariables,andthemulti-objectivemethodofNSGA-Ⅱastheoptimizer.Thusamulti-objectiveoptimizationmodelfortherollshiftingstrategyisbuilt.Thesimulationresultsshowthatworkrollshiftingcanmakewearcontoursmooth,andadish-shapedwearcontourwithoutseverelocalwearcanbeachievedbytherollshiftingstrategywithvaryingstroke.OptimizationexperimentationshowsthatbymeansofNSGA-Ⅱ,agoodPareto-optimalfrontcanbeobtained,whichsuggestsaseriesofalternativesolutionsforrollshiftingstrategyoptimization.Theexperimentationalsoshowsthatthereisaconflictbetweenthetwoobjectives.Finally,applicationcasesconfirmthefeasibilityofthemulti-objectiveapproach,whichcanimprovethestripprofile,reduceedgewavesandextendtherollingmilesofarollingcampaign.

简介：