物流系统设计的选址模型介绍(英文版)(ppt 32页).ppt

Facilitylocationmodelsfordistributionsystemdesign,物流系统设计的选址模型,IntroductionTypesofmodelsGeneralmethods,Thedesignofthedistributionsystemisastrategicissueforalmosteverycompany.Theproblemoflocatingfacilitiesandallocatingcustomerscoversthecoretopicsofdistributionsystemdesign.,Introduction,Industrialfirmsmustlocatefabrication(制造厂)andassemblyplants(组装厂)aswellaswarehouses(仓库).Storeshavetobelocatedbyretailoutlets(零售网点).Theabilitytomanufactureandmarketitsproductsisdependentinpartonthelocationofthefacilities.Similarly,governmentagencieshavetodecideaboutthelocationofoffices,schools,hospitals,firestations,etc.Ineverycase,thequalityoftheservicesdependsonthelocationofthefacilitiesinrelationtootherfacilities.,Typesofmodels,Theproblemoflocatingfacilitiesisnotnewtotheoperationsresearchcommunity(运筹学);thechallengeofwheretobestsitefacilitieshasinspiredarich,colorfulandevergrowingbodyofliterature.Tocopewiththemultitudeofapplications(众多应用)encounteredinthebusinessworldandinthepublicsector,aneverexpandingfamilyofmodelshasemerged.,Facilitylocationmodelscanbebroadlyclassifiedasfollows:,Theshapeortopographyofthesetofpotentialplantsyieldsmodelsintheplane,networklocationmodels(网络选址模型),anddiscretelocation(离散选址)ormixed-integerprogrammingmodels(混合正数规划模型),respectively.,Objectives(目标函数)maybeeitheroftheminsumortheminmaxtype.Minsummodelsaredesignedtominimizeaveragedistanceswhileminmaxmodelshavetominimizemaximumdistances.Predominantly(此外),minsummodelsembracelocationproblemsofprivatecompanieswhileminmaxmodelsfocusonlocationproblemsarisinginthepublicsector.,Modelswithoutcapacityconstraintsdonotrestrict(限制)demandallocation.Ifcapacityconstraintsforthepotentialsiteshavetobeobeyeddemandhastobeallocatedcarefully.Inthelattercasewehavetoexaminewhethersingle-sourcing(单来源)ormultiple-sourcing(多来源)isessential.,Single-stagemodels(单阶段模型)focusondistributionsystemscoveringonlyonestageexplicitly.Inmulti-stagemodels(多阶段模型)theflowofgoodscomprisingseveralhierarchical(层次)stageshastobeexamined.,Single-productmodels(单产品模型)arecharacterizedbythefactthatdemand,costandcapacityforseveralproductscanbeaggregatedtoasinglehomogeneousproduct.Ifproductsareinhomogeneoustheireffectonthedesignofthedistributionsystemhastobeanalyzed,viz.multi-productmodels(多产品模型)havetobestudied.,Locationmodelsbaseontheassumptionthatdemandisinelastic(无弹性的),thatis,demandisindependentofspatialdecisions.Ifdemandiselastic(弹性的)therelationshipbetween,e.g.,distanceanddemandhastobetakenintoaccountexplicitly.Inthelattercasecostminimization(成本最小)hastobereplacedthrough,forexample,revenuemaximization(收益最大).,Staticmodels(静态模型)trytooptimizesystemperformance(性能)foronerepresentative(代表)period.Bycontrastdynamicmodels(动态模型)reflectdata(cost,demand,capacities,etc.)varyingovertimewithinagivenplanninghorizon.,Inpracticemodel(实践模型)inputisusuallynotknownwithcertainty.Dataarebasedonforecastsand,hence,arelikelytobeuncertain.Asaconsequence,wehaveeitherdeterministicmodels(确定模型)ifinputis(assumedtobe)knownwithcertaintyorprobabilisticmodels(概率模型)ifinputissubjecttouncertainty.,Inclassicalmodelsthequalityofdemandallocationismeasuredonisolationforeachpairofsupplyanddemandpoints.Unfortunately,ifdemandissatisfiedthroughdeliverytours(运输,投递)then,forinstance,deliverycostcannotbecalculatedforeachpairofsupplyanddemandpointsseparately.Combinedlocation/routingmodels(选址/路线模型)elaborateonthisinterrelationship.,Generalmethods,AHP(AnalyticHierarchyProcess)层次分析法FuzzyClustering模糊聚类法Cross-medianmethod交叉中值法gravitymethod重心法P-medianmethodP-中值法Systemicarithmetic系统模拟法Geneticalgorithm(GA)遗传算法Theshortestpathmethod最短路径法SimulatedAnnealing(SA)模拟退火算法,TheAnalyticHierarchyProcess(AHP)isastructuredtechniquefordealingwithcomplexdeciision.Ratherthanprescribingacorrectdecision,theAHPhelpsthedecisionmakersfindonethatbestsuitstheirgoalandtheirunderstandingoftheproblem.Basedonmathematicsandpsychology,theAHPwasdevelopedbyThomasL.Saatyinthe1970sandhasbeenextensivelystudiedandrefinedsincethen.Itprovidesacomprehensive(全面)andrationalframework（合理的框架）forstructuringadecisionproblem（结构化决策问题）,forrepresentingandquantifyingitselements,forrelatingthoseelementstooverallgoals,andforevaluatingalternativesolutions.Itisusedaroundtheworldinawidevarietyofdecisionsituations,infieldssuchasgovernment,business,industry,healthcare,andeducation.,AHP,FuzzyClustering,Fuzzyclusteringisaclassofalgorithmsforclusteranalysisinwhichtheallocationofdatapointstoclustersisnothard(all-or-nothing)butfuzzyinthesamesenseasfuzzylogic.Inhardclustering,dataisdividedintodistinctclusters,whereeachdataelementbelongstoexactlyonecluster.Infuzzyclustering(alsoreferredtoassoftclustering),dataelementscanbelongtomorethanonecluster,andassociatedwitheachelementisasetofmembershiplevels(隶属关系).Theseindicatethestrengthoftheassociationbetweenthatdataelementandaparticularcluster.Fuzzyclusteringisaprocessofassigningthesemembershiplevels,andthenusingthemtoassigndataelementstooneormoreclusters.,gravitymethod,总运费=设施与客户之间的直线距离(欧几里德距离)需求量,对上式分别对x，y求偏微分，可以求出下面的一对隐含有最优解的等式，应用这两个等式通过迭代的方法分别对x，y进行求解，即可得最优解。,Cross-medianmethod,总费用=设施到需求点的折线距离(城市距离)需求量,上述目标函数可以用两个互不相干的部分来表述：,其中:,最优位置是由如下坐标组成的点:xs是在x方向的所有的权重wi的中值点,ys是在y方向的所有的权重wi的中值点。,Thegeneticalgorithm(GA)isasearchheuristic(启发式)thatmimics(模仿)theprocessofnaturalevolution.Thisheuristicisroutinelyusedtogenerateusefulsolutionstooptimizationandsearchproblems.Geneticalgorithmsbelongtothelargerclassofevolutionaryalgorithms(EA)(进化算法),whichgeneratesolutions(生成解决方案)tooptimizationproblemsusingtechniquesinspiredbynaturalevolution,suchasinheritance(继承),mutation(突变),selection(选择),andcrossover(杂交).,Geneticalgorithm,SimulatedAnnealing,Simulatedannealing(SA)isagenericprobabilisticmetaheuristic(启发式)fortheglobaloptimizationproblemofappliedmathematics(应用数学),namelylocatingagoodapproximation(逼近)totheglobaloptimumofagivenfunctioninalargesearchspace.Itisoftenusedwhenthesearchspaceisdiscrete(e.g.,alltoursthatvisitagivensetofcities).Forcertainproblems,simulatedannealingmaybemoreeffectivethanexhaustiveenumeration(穷举法)providedthatthegoalismerelytofindanacceptablygoodsolutioninafixedamountoftime,ratherthanthebestpossiblesolution.,MinisumMinimaxMaximin,Minisum被称为网络上的中值问题。