简介：AnovelalgorithmcalledColonyLocationAlgorithm(CLA)isproposed.Itmimicsthephenomenainbioticconmunitythatcoloniesofspeciescouldbelocatedintheplacesmostsuitabletotheirgrowth.Thefactorsworkingonthespecieslocationsuchasthenutrientofsoil,resourcecompetitionbetweenspecies,growthanddeclineprocess,andeffectonenvironmentwereconsideredinCLAviathenutrientfunction,growthanddeclinerates,environmentevaluationandfertilizationstrategy.CLAwasappliedtosolvetheclassicalassignmentproblems.ThecomputationresultsshowthatCLAcanachievetheoptimalsolutionwithhigherpossibilityandshorterrunningtime.

简介：WeconsiderafamilyofoptimalcontrolproblemswherethecontrolvariableisgivenbyaboundaryconditionofNeumanntype.Thisfamilyisgovernedbyparabolicvariationalinequalitiesofthesecondkind.Weprovethestrongconvergenceoftheoptimalcontrolandstatesystemsassociatedtothisfamilytoasimilaroptimalcontrolproblem.ThisworksolvestheopenproblemleftbytheauthorsinIFIPTC7CSMO2011.

简介：Inmanyreal-worldapplicationsofevolutionaryalgorithms,thefitnessofanindividualrequiresaquantitativemeasure.Thispaperproposesaself-adaptivelinearevolutionaryalgorithm(ALEA)inwhichweintroduceanovelstrategyforevaluatingindividual'srelativestrengthsandweaknesses.Basedonthisstrategy,searchingspaceofconstrainedoptimizationproblemswithhighdimensionsfordesignvariablesiscompressedintotwo-dimensionalperformancespaceinwhichitispossibletoquicklyidentify'good'individualsoftheperformanceforamultiobjectiveoptimizationapplication,regardlessoforiginalspacecomplexity.Thisisconsideredasourmaincontribution.Inaddition,theproposednewevolutionaryalgorithmcombinestwobasicoperatorswithmodificationinreproductionphase,namely,crossoverandmutation.Simulationresultsoveracomprehensivesetofbenchmarkfunctionsshowthattheproposedstrategyisfeasibleandeffective,andprovidesgoodperformanceintermsofuniformityanddiversityofsolutions.

简介：Nonlinearstochasticoptimalcontrolproblemsarefundamentalincontroltheory.Ageneralclassofsuchproblemscanbereducedtocomputingtheprincipaleigenfunctionofalinearoperator.Here,wedescribeanewmethodforfindingthiseigenfunctionusingamovingleast-squaresfunctionapproximation.Weuseefficientiterativesolversthatdonotrequirematrixfactorization,therebyallowingustohandlelargenumbersofbasisfunctions.Thebasesareevaluatedatcollocationstatesthatchangeoveriterati...