塔式起重机位置优化中英文对照外文翻译文献

塔式起重机位置优化中英文对照外文翻译文献塔式起重机位置优化中英文对照外文翻译文献(文档含英文原文和中文翻译)原文：LOCATIONOPTIMIZATIONFORAGROUPOFTOWERCRANESABSTRACT:Acomputerizedmodeltooptimizelocationofagroupoftowercranesispresented.Locationtions.Threesubmodelsarealsopresented.First,theinitiallocationmodelclassifiestasksintogroupsandmentalresultsandthestepsnecessaryforimplementationofthemodelarediscussed.INTRODUCTIONOnlargeconstructionprojectsseveralcranesgenerallyundertaketransportationtasks,particularlywhenasinglecranecannotprovideoverallcoverageofalldemandandsupplypoints,and/orwhenitscapacityisexceededbytheneedsofatightconstructionschedule.Manyfactorsinfluencetowercranelocation.Intheinterestsofsafetyandefficientoperation,cranesshouldbelocatedasfarapartaspossibletoavoidinterferenceandcollisions,ontheconditionthatallplannedtaskscanbeperformed.However,thisidealsituationisoftendifficulttoachieveinpractice;constrainedworkspaceandlimitationsofcranecapacitymakeitinevitablethatcraneareasoverlap.Subsequently,interferenceandcollisionscanoccurevenifcranejibsworkatdifferentlevels.Craneposition(s)tendtobedeterminedthroughtrialanderror,basedonsitetopography/shapeandoverallcoverageoftasks.Thealternativesforcranelocationcanbecomplex,somanagersremainconfrontedbymultiplechoicesandlittlequantitativereference.Cranelocationmodelshaveevolvedoverthepast20years.Warszawski(1973)establishedatime-distanceformulabywhichquantitativeevaluationoflocationwaspossible.FurusakaandGray(1984)presentedadynamicprogrammingmodelwiththeobjectivefunctionbeinghirecost,butwithoutconsiderationoflocation.GrayandLittle(1985)optimizedcranelocationinirregular-shapedbuildingswhileWijesunderaandHarris(1986)designedasimulationmodeltoreconstructoperationtimesandequipmentcycleswhenhandlingconcrete.FarrellandHover(1989)developedadatabasewithagraphicalinterfacetoassistincraneselectionandlocation.ChoiandHarris(1991)introducedanothermodeltooptimizesingletowercranelocationbycalculatingtotaltransportationtimesincurred.Emsley(1992)proposedseveralimprovementstotheChoiandHarrismodel.Apartfromthesealgorithmicapproaches,rule-basedsystemshavealsoevolvedtoassistdecisionsoncranenumbersandtypesaswellastheirsitelayout。AssumptionsSitemanagerswereinterviewedtoidentifytheirconcernsandobservecurrentapproachestothetaskathand.Further,operationswereobservedon14siteswherecraneswereintensivelyused(fourinChina,sixinEngland,andfourinScotland).Timestudieswerecarriedoutonfoursitesforsixweeks,twositesfortwoweekseach,andtwoforoneweekeach.Findingssuggestedinteraliathatfullcoverageofworkingarea,balancedworkloadwithnointerference,andgroundconditionsaremajorconsiderationsindetermininggrouplocation.Therefore,effortswereconcentratedonthesefactors(exceptgroundconditionsbecausesitemanagerscanspecifyfeasiblelocationareas).Thefollowingfourassumptionswereappliedtomodeldevelopment(detailedlater):Geometriclayoutofallsupply(S)anddemand(D)points,togetherwiththetypeandnumberofcranes,arepredetermined.ForeachS-Dpair,demandlevelsfortransportationareknown,e.g.,totalnumberoflifts,numberofliftsforeachbatch,maximumload,unloadingdelays,andsoon.Thedurationofconstructionisbroadlysimilarovertheworkingareas.ThematerialtransportedbetweenanS-Dpairishandledbyonecraneonly.MODELDESCRIPTIONThreestepsareinvolvedindeterminingoptimalpositionsforacranegroup.First,alocationgenerationmodelproducesanapproximatetaskgroupforeachcrane.Thisisthenadjustedbyataskassignmentmodel.Finally,anoptimizationmodelisappliedtoeachtowerinturntofindanexactcranelocationforeachtaskgroup.InitialLocationGenerationModelLiftCapacityand‘‘Feasible’’AreaCraneliftcapacityisdeterminedfromaradius-loadcurvewherethegreatertheload,thesmallerthecrane’soperatingradius.Assumingaloadatsupplypoint(S)withtheweightw,itscorrespondingcraneradiusisr.Acraneisthereforeunabletoliftaloadunlessitislocatedwithinacirclewithradiusr[Fig.1(a)].Todeliveraloadfrom(S)todemandpoint(D),thecranehastobepositionedwithinanellipticalarea(a)FIG.1.FeasibleAreaofCraneLocationforTaskFIG.2.Task“Closenness”enclosedbytwocircles,showninFig.1(b).Thisiscalledthefeasibletaskarea.ThesizeoftheareaisrelatedtothedistancebetweenSandD,theweightoftheload,andcranecapacity.Thelargerthefeasiblearea,themoreeasilythetaskcanbehandled.Measurementof‘‘Closeness’’ofTasksThreegeometricrelationshipsexistforanytwofeasibletaskareas,asillustratedinFig.2;namely,(a)onefullyenclosedbyanother(tasks1and2);(b)twoareaspartlyintersected(tasks1and3);and(c)twoareasseparated(tasks2and3).Asindicatedincases(a)and(b),bybeinglocatedinareaA,acranecanhandlebothtasks1and2,andsimilarly,withinB,tasks1and3.However,case(c)showsthattasks2and3aresofarfromeachotherthatasingletowercraneisunabletohandlebothwithoutmovinglocation;somorethanonecraneorgreaterliftingcapacityisrequired.Theclosenessoftaskscanbemeasuredbythesizeofoverlappingarea,e.g.,task2isclosertotask1thantask3becausetheoverlappingareabetweentasks1and2islargerthanthatfor1and3.Thisconceptcanbeextendedtomeasureclosenessofatasktoataskgroup.Forexample,areaCinFig.2(b)isafeasibleareaofataskgroupconsistingofthreetasks,wheretask5issaidtobeclosertothetaskgroupthantask4sincetheoverlappingareabetweenCandDislargerthanthatbetweenCandE.Iftask5isaddedtothegroup,thefeasibleareaofthenewgroupwouldbeD,showninFigure2(c).GroupingTasksintoSeparatedClassesIfnooverlappingexistsbetweenfeasibleareas,twocranesarerequiredtohandleeachtaskseparatelyifnootheralternatives—suchascraneswithgreaterliftingcapacityorreplanningofsitelayout—areallowed.Similarly,threecranesarerequirediftherearethreetasksinwhichanytwohavenooverlappingareas.Generally,taskswhosefeasibleareasareisolatedmustbehandledbyseparatecranes.Theseinitialtasksareassignedrespectivelytodifferent(crane)taskgroupsasthefirstmemberofthegroup,thenallothertasksareclusteredaccordingtoproximitytothem.Obviously,tasksfurthestapartaregivenpriorityasinitialtasks.Whenmultiplechoicesexist,computerrunningtimecanbereducedbyselectingtaskswithsmallerfeasibleareasasinitialtasks.Themodelprovidesassistanceinthisrespectbydisplayinggraphicallayoutoftasksandalistofthesizeoffeasibleareaforeach.Afterassigninganinitialtasktoagroup,themodelsearchesfortheclosestremainingtaskbycheckingthesizeofoverlappingarea,thenplacesitintothetaskgrouptoproduceanewfeasibleareacorrespondingtotherecentlygeneratedtaskgroup.Theprocessisrepeateduntiltherearenotasksremaininghavinganoverlappingareawithinthepresentgroup.Thereafter,themodelswitchestosearchforthenextgroupfromthepoolofalltasks,theprocessbeingcontinueduntilalltaskgroupshavebeenconsidered.Ifataskfailstobeassignedtoagroup,amessageisproducedtoreportwhichtasksareleftsotheusercansupplymorecranesor,alternatively,changethetasklayoutandrunthemodelagain.InitialCraneLocationWhentaskgroupshavebeencreated,overlappingareascanbeformed.Thus,theinitiallocationsareautomaticallyatthegeometriccentersofthecommonfeasibleareas,oranywherespecifiedbytheuserwithincommonfeasibleareas.TaskAssignmentModelGrouplocationisdeterminedbygeometric‘‘closeness.’’However,onecranemightbeoverburdenedwhileothersareidle.Furthermore,cranescanofteninterferewitheachothersotaskassignmentisappliedtothosetasksthatcanbereachedbymorethanonecranetominimizethesepossibilities.FeasibleAreasfromLastThreeSetsofInputshapeandsizeoffeasibleareas,illustratedinFig.9.Inthiscasestudy,fromthedataandgraphicoutput,theusermaybecomeawarethatoptimallocationsledbytestsets1,2,and3(Fig.3)arethebestchoices(balancedworkload,conflictpossibility,andefficientoperation).Alternatively,inconnectionwithsiteconditionssuchasavailabilityofspaceforthecranepositionandgroundconditionsforthefoundation,siteboundarieswererestricted.Consequently,oneofthecraneshadtobepositionedinthebuilding.Inthisrespect,theoutcomesresultingfromset4wouldbeagoodchoiceintermsofareasonableconflictindexandstandarddeviationofworkload,providedthataclimbingcraneisavailableandthebuildingstructureiscapableofsupportingthiskindofcrane.Otherwise,set5resultswouldbepreferablewiththestationarytowercranelocatedintheelevatorwell,butatthecostofsufferingthehighpossibilityofinterferenceandunbalancedworkloadsOverallcoverageoftaskstendstobethemajorcriterioninplanningcranegrouplocation.However,thisrequirementmaynotdetermineoptimallocation.Themodelhelpsimproveconventionallocationmethods,basedontheconceptthattheworkloadforeachcraneshouldbebalanced,likelihoodofinterferenceminimized,andefficientoperationachieved.Todothis,threesubmodelswerehighlighted.First,byclassifyingallness’’anoveralllayoutisproduced.Second,basedonasetofpointslocatedrespectivelyinthefeasibleareas(initiallocation),thetaskassignmentreadjuststhegroupstoproducenewoptimaltaskgroupswithsmoothedworkloadsandleastpossibilityofconflicts,togetherwithfeasibleareascreated.Finally,optimizationisappliedforeachcraneonebyonetofindanexactlocationintermsofhooktransporttimeinthreedimensions.Experimentalresultsindicatethatthemodelperformssatisfactorily.Inadditiontotheimprovementonsafetyandaverageefficiencyofallcranes,10–40%savingsoftotalhookstransportationtimecanbeachieved.Efforthasbeenmadetomodelthekeycriteriaforlocatingagroupoftowercranes,andtworealsitedatahavebeenusedtotestthemodel.However,itdoesnotcapturealltheexpertiseandexperienceofsitemanagers;otherfactorsrelatingtobuildingstructure,foundationconditions,laydownspacesformaterials,accessibilityofadjoiningpropertiesandsoon,alsocontributetotheproblemoflocations.Therefore,thefinaldecisionshouldbemadeinconnectionwiththesefactors.翻译：一组塔式起重机的位置优化摘要计算机模型能使一组塔机位置更加优化。合适的位置条件能平衡工作载荷，降低塔机之间碰撞的可能性，提高工作效率。这里对三个子模型进行了介绍。首先，把初始位置模型分组，根据几何的相似性，确认每个塔机的合适位置。然后，调整前任务组的平衡工作载荷并降低碰撞的可能性。最后，运用一个单塔起重机优化模型去寻找吊钩运输时间最短的位置。本文对模型完成的实验结果和必要的步骤进行了讨论。引言在大规模的建设工程中特别是当一个单塔起动机不能全面的完成重要的任务要求时或者当塔机不能完成紧急的建设任务时通常是由几个塔机同时完成任务。影响塔机的因素很多。从操作效率和安全方面考虑，如果所有计划的任务都能执行，应将塔机尽可能的分开，避免互相干扰和碰撞。然而这种理想的情况在实践中很难成功，因为工作空间的限制和塔机的耐力有限使塔机的工作区域重叠是不可避免的。因此，即使起重机的铁臂在不同的水平工作面也会发生互相干扰和碰撞。在地形选址和全面的完成任务的基础上，通过反复实验来决定塔式起重机的合适位置。起重机位置的选择很复杂，因此，管理人员仍然面临着多样的选择和少量的定量参考。在过去的20年里，起重机位置模型逐步形成。Warszawski(1973)尝试尽可能用时间与距离来计算塔机的位置。FurusakaandGray(1984)提出用目标函数和被雇用成本规划动态模型，但是没考虑到位置。GrayandLittle(1985)在处理不规则的混凝土建筑物时候，设置位置优化的塔式起动机。然而，WijesunderaandHarris(1986)在处理具体的任务时减少了操作时间和延长了设备使用周期时设计了一种模拟模型。FarrellandHover(1989)开发了带有图解界面的数据库，来协助起动机的位置的选择。ChoiandHarris(1991)通过计算运输所须的全部时间来提出另一种优化单塔起重机位置优化。Emsley(1992)改进了ChoiandHarris提出的模型。除了在计算方法相似外，起重机的数量类型和设计系统规则也得以提高假设采访网站管理员关于他们的公司和观察到手上的工作电流的方法。另外观察起重机集中在14个操作站点的运用。(在中国是4个，在英格兰是6个，在苏格兰是4个)。研究设备放在4个站点时间为6个星期，两个站点用两个星期时间。调查结果显示尤其是在全面覆盖工作领域，没有干扰，平衡工作载荷和地面情况是决定塔机位置重要的原因。因此，重点在这些因素上（除了地面情况因为站点管理员能明确说明合适的区域位置）。下面4种假设被应用于模型发展（以后的详尽）预先确定所有供应点和需求点的几何布局、起重机的类型和数量。对于每个供应点和需求点，运输需求水平是已知的。例如，起重机的总数、每组起重机的数量、最大限度的装载、延迟卸货等等。在建设时期和工作区域大体相同。只用一个起重机运输供应点与需求点之间的物料。模型描述决定起重机理想的位置有三个位置条件。首先用位置模型产生一个相似的任务组，然后用任务分配模型调整，最后优化模型轮流并运用到每个任务组中的准确位置。初始位置生成模型起重机的起升能力和合适的区域起重机的升起能力取决于曲线的半径，负荷量越大，起重机的操作半径越小。假设供应点的负荷量是w,相应的起重机半径是r。一个起重机若不能承受装载除非它的半径在圆内（图1）。从供应点传送一个装载需求点，必须把起重机放在两个重合的椭圆区域，如图表1(b)，这是合适任务区域。区域的大小与供应点和需求点的距离、负荷量、起重机的耐力有关。合当的区域越大，越容易完成任务。相近任务的测量对于任何两种合适的任务区域存在3种几何关系，如图解2.也就是说，(a)一个图与另个图完全重合（任务1与2）。(b)两个区域部分相交（任务1与3）。（c）两个区域分开（任务2与3）。如指出的实例a与b,起重机被放在区域A中能完成任务1和任务2，同样的，在区域B中,能完成任务1和3.然而实例c显示，任务2和3距离太远，一个单独的起重机在没有移动位置的