Chapter-1-Basic-Simulation-Modeling-ximb1章基本仿真建模ximb資料課件

Chapter1

BasicSimulationModeling1SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingCONTENTS1.1TheNatureofSimulation1.2Systems,Models,andSimulation1.3Discrete-EventSimulation1.4SimulationofaSingle-ServerQueueingSystem1.5SimulationofanInventorySystem1.6AlternativeApproachestoModelingandCodingSimulations1.7StepsinaSoundSimulationStudy1.8OtherTypesofSimulation1.9Advantages,Disadvantages,andPitfallsofSimulation2SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.1THENATUREOFSIMULATIONSimulation:Imitatetheoperationsofafacilityorprocess,usuallyviacomputerWhat’sbeingsimulatedisthesystemTostudysystem,oftenmakeassumptions/approximations,bothlogicalandmathematical,abouthowitworksTheseassumptionsformamodelofthesystemIfmodelstructureissimpleenough,couldusemathematicalmethodstogetexactinformationonquestionsofinterest—analyticalsolution3SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.1TheNatureofSimulation(cont’d.)Butmostcomplexsystemsrequiremodelsthatarealsocomplex(tobevalid)Mustbestudiedviasimulation—evaluatemodelnumericallyandcollectdatatoestimatemodelcharacteristicsExample:ManufacturingcompanyconsideringextendingitsplantBuilditandseeifitworksout?Simulatecurrent,expandedoperations—couldalsoinvestigatemanyotherissuesalongtheway,quicklyandcheaply4SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.1TheNatureofSimulation(cont’d.)Some(notall)applicationareasDesigningandanalyzingmanufacturingsystemsEvaluatingmilitaryweaponssystemsortheirlogisticsrequirementsDetermininghardwarerequirementsorprotocolsforcommunicationsnetworksDetermininghardwareandsoftwarerequirementsforacomputersystemDesigningandoperatingtransportationsystemssuchasairports,freeways,ports,andsubwaysEvaluatingdesignsforserviceorganizationssuchascallcenters,fast-foodrestaurants,hospitals,andpostofficesReengineeringofbusinessprocessesDeterminingorderingpoliciesforaninventorysystemAnalyzingfinancialoreconomicsystems5SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.1TheNatureofSimulation(cont’d.)Use,popularityofsimulationSeveralconferencesdevotedtosimulation,notablytheWinterSimulationConference()SurveysofuseofOR/MStechniques(examples…)Longitudinalstudy(1973-1988):Simulationconsistentlyrankedasoneofthethreemostimportanttechniques1294papersinInterfaces(2019):Simulationwassecondonlytothebroadcategoryof“mathprogramming”6SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.1TheNatureofSimulation(cont’d.)Impedimentstoacceptance,useofsimulationModelsoflargesystemsareusuallyverycomplexButnowhavebettermodelingsoftware…moregeneral,flexible,butstill(relatively)easytouseCanconsumealotofcomputertimeButnowhavefaster,bigger,cheaperhardwaretoallowformuchbetterstudiesthanjustafewyearsago…thistrendwillcontinueHowever,simulationwillalsocontinuetopushtheenvelopeoncomputingpowerinthatweaskmoreandmoreofoursimulationmodelsImpressionthatsimulationis“justprogramming”There’salotmoretoasimulationstudythanjust“coding”amodelinsomesoftwareandrunningittoget“theanswer”Needcarefuldesignandanalysisofsimulationmodels–simulationmethodology7SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.2SYSTEMS,MODELS,ANDSIMULATIONSystem:Acollectionofentities(people,parts,messages,machines,servers,…)thatactandinteracttogethertowardsomeend(SchmidtandTaylor,1970)Inpractice,dependsonobjectivesofstudyMightlimittheboundaries(physicalandlogical)ofthesystemJudgmentcall:levelofdetail(e.g.,whatisanentity?)Usuallyassumeatimeelement–dynamicsystemStateofasystem:CollectionofvariablesandtheirvaluesnecessarytodescribethesystematthattimeMightdependondesiredobjectives,outputperformancemeasuresBankmodel:Couldincludenumberofbusytellers,timeofarrivalofeachcustomer,etc.8SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.2Systems,Models,andSimulation(cont’d.)TypesofsystemsDiscreteStatevariableschangeinstantaneouslyatseparatedpointsintimeBankmodel:StatechangesoccuronlywhenacustomerarrivesordepartsContinuousStatevariableschangecontinuouslyasafunctionoftimeAirplaneflight:Statevariableslikeposition,velocitychangecontinuouslyManysystemsarepartlydiscrete,partlycontinuous9SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingWaystostudyasystem1.2Systems,Models,andSimulation(cont’d.)Simulationis“methodoflastresort?”Maybe…Butwithsimulationthere’snoneed(orlessneed)to“l(fā)ookwherethelightis”10SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.2Systems,Models,andSimulation(cont’d.)ClassificationofsimulationmodelsStaticvs.dynamicDeterministicvs.stochasticContinuousvs.discreteMostoperationalmodelsaredynamic,stochastic,anddiscrete–willbecalleddiscrete-eventsimulationmodels11SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3DISCRETE-EVENTSIMULATIONDiscrete-eventsimulation:ModelingofasystemasitevolvesovertimebyarepresentationwherethestatevariableschangeinstantaneouslyatseparatedpointsintimeMoreprecisely,statecanchangeatonlyacountablenumberofpointsintimeThesepointsintimearewheneventsoccurEvent:InstantaneousoccurrencethatmaychangethestateofthesystemSometimesgetcreativeaboutwhatan“event”is…e.g.,endofsimulation,makeadecisionaboutasystem’soperationCaninprinciplebedonebyhand,butusuallydoneoncomputer12SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3Discrete-EventSimulation(cont’d.)Example:Single-serverqueueEstimateexpectedaveragedelayinqueue(line,notservice)StatevariablesStatusofserver(idle,busy)–neededtodecidewhattodowithanarrivalCurrentlengthofthequeue–toknowwheretostoreanarrivalthatmustwaitinlineTimeofarrivalofeachcustomernowinqueue–neededtocomputetimeinqueuewhenservicestartsEventsArrivalofanewcustomerServicecompletion(anddeparture)ofacustomerMaybe–end-simulationevent(a“fake”event)–whetherthisisaneventdependsonhowsimulationterminates(amodelingdecision)13SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.1Time-AdvanceMechanismsSimulationclock:Variablethatkeepsthecurrentvalueof(simulated)timeinthemodelMustdecideon,beconsistentabout,timeunitsUsuallynorelationbetweensimulatedtimeand(real)timeneededtorunamodelonacomputerTwoapproachesfortimeadvanceNext-eventtimeadvance(usuallyused)…describedindetailbelowFixed-incrementtimeadvance(seldomused)…DescribedinAppendix1AGenerallyintroducessomeamountofmodelingerrorintermsofwheneventsshouldoccurvs.dooccurForcesatradeoffbetweenmodelaccuracyandcomputationalefficiency14SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.1Time-AdvanceMechanisms(cont’d.)Moreonnext-eventtimeadvanceInitializesimulationclockto0Determinetimesofoccurrenceoffutureevents–eventlistClockadvancestonext(mostimminent)event,whichisexecutedEventexecutionmayinvolveupdatingeventlistContinueuntilstoppingruleissatisfied(mustbeexplicitlystated)Clock“jumps”fromoneeventtimetothenext,anddoesn’t“exist”fortimesbetweensuccessiveevents…periodsofinactivityareignored15SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.1Time-AdvanceMechanisms(cont’d.)Next-eventtimeadvanceforthesingle-serverqueueti=timeofarrivalofithcustomer(t0=0)Ai=ti–ti-1=interarrivaltimebetween(i-1)standithcustomers(usuallyassumedtobearandomvariablefromsomeprobabilitydistribution)Si=service-timerequirementofithcustomer(anotherrandomvariable)Di=delayinqueueofithcustomerCi=ti+Di+Si=timeithcustomercompletesserviceanddepartsej=timeofoccurrenceofthejthevent(ofanytype),j=1,2,3,…Possibletraceofevents(detailednarrativeintext)16SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.2ComponentsandOrganizationofaDiscrete-EventSimulationModelEachsimulationmodelmustbecustomizedtotargetsystemButthereareseveralcommoncomponents,generalorganizationSystemstate–variablestodescribestateSimulationclock–currentvalueofsimulatedtimeEventlist–timesoffutureevents(asneeded)Statisticalcounters–toaccumulatequantitiesforoutputInitializationroutine–initializemodelattime0Timingroutine–determinenexteventtime,type;advanceclockEventroutines–carryoutlogicforeacheventtypeLibraryroutines–utilityroutinestogeneraterandomvariates,etc.Reportgenerator–tosummarize,reportresultsatendMainprogram–tiesroutinestogether,executestheminrightorder17SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.2ComponentsandOrganizationofaDiscrete-EventSimulationModel(cont’d.)18SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.3.2ComponentsandOrganizationofaDiscrete-EventSimulationModel(cont’d.)MoreonentitiesObjectsthatcomposeasimulationmodelUsuallyincludecustomers,parts,messages,etc.…mayincluderesourceslikeserversCharacterizedbydatavaluescalledattributesForeachentityresidentinthemodelthere’sarecord(row)inalist,withtheattributesbeingthecolumnsApproachestomodelingEvent-scheduling–asdescribedabove,codedingeneral-purposelanguageProcess–focusesonentitiesandtheir“experience,”usuallyrequiresspecial-purposesimulationsoftware19SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4SIMULATIONOFASINGLE-SERVERQUEUEINGSYSTEMWillshowhowtosimulateaspecificversionofthesingle-serverqueueingsystemBookcontainscodeinFORTRANandC…slideswillfocusonlyonCversionThoughsimple,itcontainsmanyfeaturesfoundinallsimulationmodels20SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.1ProblemStatementRecallsingle-serverqueueingmodelAssumeinterarrivaltimesareindependentandidenticallydistributed(IID)randomvariablesAssumeservicetimesareIID,andareindependentofinterarrivaltimesQueuedisciplineisFIFOStartemptyandidleattime0Firstcustomerarrivesafteraninterarrivaltime,notattime0Stoppingrule:Whennthcustomerhascompleteddelayinqueue(i.e.,entersservice)…nwillbespecifiedasinput21SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.1ProblemStatement(cont’d.)QuantitiestobeestimatedExpectedaveragedelayinqueue(excludingservicetime)ofthencustomerscompletingtheirdelaysWhy“expected?”Expectedaveragenumberofcustomersinqueue(excludinganyinservice)Acontinuous-timeaverageAreaunderQ(t)=queuelengthattimet,dividedbyT(n)=timesimulationends…seebookforjustificationanddetailsExpectedutilization(proportionoftimebusy)oftheserverAnothercontinuous-timeaverageAreaunderB(t)=server-busyfunction(1ifbusy,0ifidleattimet),dividedbyT(n)…justificationanddetailsinbookManyothersarepossible(maxima,minima,timeornumberinsystem,proportions,quantiles,variances…)Important:Discrete-timevs.continuous-timestatistics22SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanationGiven(fornow)interarrivaltimes(alltimesareinminutes):0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Givenservicetimes:2.0,0.7,0.2,1.1,3.7,0.6,…n=6delaysinqueuedesired“Hand”simulation:Displaysystem,statevariables,clock,eventlist,statisticalcounters…allafterexecutionofeacheventUseabovelistsofinterarrival,servicetimesto“drive”simulationStopwhennumberofdelayshitsn=6,computeoutputperformancemeasures23SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Statusshownisafterallchangeshavebeenmadeineachcase…Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…24SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…25SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…26SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…27SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…28SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…29SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…30SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…31SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…32SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…33SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…34SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…35SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…36SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.2IntuitiveExplanation(cont’d)Interarrivaltimes: 0.4,1.2,0.5,1.7,0.2,1.6,0.2,1.4,1.9,…Servicetimes: 2.0,0.7,0.2,1.1,3.7,0.6,…Finaloutputperformancemeasures: Averagedelayinqueue=5.7/6=0.95min./cust. Time-averagenumberinqueue=9.9/8.6=1.15custs. Serverutilization=7.7/8.6=0.90(dimensionless)37SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.3ProgramOrganizationandLogicCprogramtodothismodel(FORTRANaswellisinbook)Eventtypes:1forarrival,2fordepartureModularizeforinitialization,timing,events,library,report,mainChangesfromhandsimulation:Stoppingrule:n=1000(ratherthan6)Interarrivalandservicetimes“drawn”fromanexponentialdistribution(meanb=1forinterarrivals,0.5forservicetimes)DensityfunctionCumulativedistributionfunction38SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.3ProgramOrganizationandLogic(cont’d.)Howto“draw”(orgenerate)anobservation(variate)fromanexponentialdistribution?Proposal:Assumeaperfectrandom-numbergeneratorthatgeneratesIIDvariatesfromacontinuousuniformdistributionon[0,1]…denotedtheU(0,1)distribution…seeChap.7Algorithm:1.GeneratearandomnumberU2.ReturnX=–blnUProofthatalgorithmiscorrect:39SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.5CProgram;

1.4.6SimulationOutputandDiscussionRefertopp.30,31,42-48inthebook(Figures1.8,1.9,1.19-1.27)andthefilemm1.cFigure1.19–externaldefinitions(attopoffile)Figure1.20–functionmainFigure1.21–functioninitializeFigure1.22–functiontimingFigure1.23–functionarrive(flowchart:Figure1.8)Figure1.24–functiondepart(flowchart:Figure1.9)Figure1.25–functionreportFigure1.26–functionupdate_time_avg_statsFigure1.27–functionexponFigure1.28–outputreportmm1.outArethese“the”answers?Steady-statevs.terminating?Whatabouttimeinqueuevs.justtimeinsystem?40SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.7AlternativeStoppingRulesStopsimulationat(exactly)time8hours(=480minutes),ratherthanwheneverndelaysinqueuearecompletedBefore,finalvalueofsimulationclockwasarandomvariableNow,numberofdelayscompletedwillbearandomvariableIntroduceanartificial“end-simulation”event(type3)ScheduleitoninitializationEventroutineisreportgeneratorBesuretoupdatecontinuous-timestatisticstoendChangesinCcode(everythingelseisthesame)Figure1.33–externaldefinitionsFigure1.34–functionmainFigure1.35–functioninitializeFigure1.36–functionreportFigure1.37–outputreportmm1alt.out41SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.4.8DeterminingtheEventsandVariablesForcomplexmodels,itmightnotbeobviouswhattheeventsareEvent-graphmethod(Schruben1983,andsubsequentpapers)givesformalgraph-theoreticmethodofanalyzingeventstructureCananalyzewhatneedstobeinitialized,possibilityofcombiningeventstosimplifymodelSoftwarepackage(SIGMA)tobuild,executeasimulationmodelviaevent-graphrepresentation42SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.5SIMULATIONOFANINVENTORYSYSTEM;

1.5.1ProblemStatementSingle-productinventoryDecidehowmanyitemstohaveininventoryforthenext

n=120months;initially(time0)have60itemsonhandDemandsagainstinventoryOccurwithinter-demandtime~exponentialwithmean0.1monthDemandsize=1,2,3,4withresp.probabilities1/6,1/3,1/3,1/6Inventoryreview,reorder–stationary(s,S)policy…atbeginningofeachmonth,reviewinventorylevel=IIfI

s,don’torder(sisaninputconstant);noorderingcostIfI<s,orderZ=S–Iitems(Sisaninputconstant,order“upto”S);orderingcost=32+3Z;deliverylag~U(0.5,1)month43SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.5.1ProblemStatement(cont’d.)Demandinexcessofcurrent(physical)inventoryisbacklogged…so(accounting)inventorycouldbe<0LetI(t)be(accounting)inventorylevelattimet(+,0,–)I+(t)=max{I(t),0}=numberofitemsphysicallyonhandattimetI–(t)=max{–I(t),0}=numberofitemsinbacklogattimetHoldingcost:Incur$1peritempermonthin(positive)inventoryTime-average(permonth)holdingcost=Shortagecost:Incur$5peritempermonthinbacklogTime-average(permonth)backlogcost=Averagetotalcostpermonth:Addordering,holding,shortagecostspermonthTrydifferent(s,S)combinationstotrytoreducetotalcost44SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.5.2ProgramOrganizationandLogicStatevariables:Inventorylevel,amountofanoutstandingorder,timeofthelast(mostrecent)eventEvents:1.Arrivalofanorderfromthesupplier2.Demandfortheproduct3.Endofthesimulationaftern=120months4.Inventoryevaluation(maybeordering)atbeginningofamonthRandomvariatesneededInterdemandtimes:exponential,asinqueueingmodelDeliverylags~U(0.5,1):0.5+(1–0.5)U,whereU~U(0,1)Demandsizes:Split[0,1]intosubintervalsofwidth1/6,1/3,1/3,1/6;generateU~U(0,1);seewhichsubintervalUfallsin;returnX=1,2,3,or4,respectivelyWhytheorderingofeventtypes3and4?45SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.5.4CProgram;

1.5.5SimulationOutputandDiscussionRefertopp.64-66,73-79inthebook(Figures1.43-1.46,1.57-1.67)andthefileinv.cFigure1.57–externaldefinitions(attopoffile)Figure1.58–functionmainFigure1.59–functioninitializeFigure1.60–functionorder_arrival(flowchart:Figure1.43)Figure1.61–functiondemand(flowchart:Figure1.44)Figure1.62–functionevaluate(flowchart:Figure1.45)Figure1.63–functionreportFigure1.64–functionupdate_time_avg_stats(flowchart:Figure1.46)Figure1.65–functionrandom_integerFigure1.66–functionuniformFigure1.67–outputreportinv.outReactionofindividualcostcomponentstochangesinsandS…overall?Uncertaintyinoutputresults(thiswasjustonerun)?46SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.6ALTERNATIVEAPPROACHESTOMODELINGANDCODINGSIMULATIONSParallelanddistributedsimulationVariouskindsofparallelanddistributedarchitecturesBreakupasimulationmodelinsomeway,runthedifferentpartssimultaneouslyondifferentparallelprocessorsDifferentwaystobreakupmodelBysupportfunctions–random-numbergeneration,variategeneration,event-listmanagement,eventroutines,etc.Decomposethemodelitself;assigndifferentpartsofmodeltodifferentprocessors–message-passingtomaintainsynchronization,orforgetsynchronizationanddo“rollbacks”ifnecessary…“virtualtime”Web-basedsimulationCentralsimulationengine,submit“jobs”overthewebWide-scopeparallel/distributedsimulation47SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.7STEPSINASOUNDSIMULATIONSTUDY48SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingSTEPSINASOUNDSIMULATIONSTUDYNowthatwehavelookedinsomedetailattheinnerworkingsofadiscrete-eventsimulation.Weneedtostepbackandrealizethatmodelprogrammingisjustpartoftheoverallefforttodesignoranalyzeacomplexsystembysimulation.Attentionmustbepaidtoavarietyofotherconcernssuchasmodelingsystemrandomness,validation,statisticalanalysisofsimulationoutputdataandprojectmanagement.Figure1.46showsthestepsthatwillcomposeatypical,soundsimulationstudy[seealsoBanksetal.(2019,pp.14-18)andLaw(2019)].49SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingThenumberbesidethesymbolrepresentingeachstepreferstothemoredetaileddescriptionofthatstepbelow.Notethatasimulationstudyisnotasimplesequentialprocess.Asoneproceedswiththestudy,itmaybenecessarytogobacktoapreviousstep.1. Formulatetheproblemandplanthestudy.Problemofinterestisstatedbymanager.Problemmaynotbestatedcorrectlyorinquantitativeterms.Aninteractiveprocessisoftennecessary50SimulationModelingandAnalysis–Chapter1–BasicSimulationModeling1.Formulateproblemandplanthestudy2.Collectdataanddefineamodel4.ConstructacomputerprogrammeandverifyAssumptionsdocumentvalid?3.5.MakepilotrunsProgrammedModelvalid?6.7.Designexperiments8.Makeproductionruns9.Analyzeoutputdata10.Document,present,anduseresultsYesYesNoNoFIGURE1.46Stepsinasimulationstudy51SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingb. Oneormorekickoffmeetingsforthestudyareconducted,withtheprojectmanager,thesimulationanalysts,andsubject-matterexperts(SMEs)inattendance.Thefollowingissuesarediscussed:OverallobjectivesofthestudySpecificquestionstobeansweredbythestudy(requiredtodecidelevelofmodeldetail)PerformancemeasuresthatwillbeusedtoevaluatetheefficacyofdifferentsystemconfigurationsScopeofthemodelSystemconfigurationstobemodeled(requiredtodecidegeneralityofsimulationprogramme)Timeframeforthestudyandtherequiredresources52SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingc. Selectthesoftwareforthemodel(seeChap.3)2.Collectdataanddefineamodel.Collectinformationonthesystemlayoutandoperatingprocedures.Nosinglepersonordocumentissufficient.Somepeoplemayhaveinaccurateinformation—makesurethattrueSMEsareidentified.Operatingproceduresmaynotbeformalized.b. Collectdata(ifpossible)tospecifymodelparametersandinputprobabilitydistributions(seeChap.6).53SimulationModelingandAnalysis–Chapter1–BasicSimulationModelingc. Delineatetheaboveinformationanddatainan"assumptionsdocument,"whichistheconceptualmodel(seeSec.5.4.3).d. Collectdata(ifpossible)ontheperformanceoftheexistingsystem(forvalidationpurposesinStep6).e. Choosingthelevelofmodeldetail(seeSec.5.2),whichisanart,shoulddependonthefollowing:ProjectobjectivesPerformancemeasuresDataavailabilityCredibilityconcernsComputerconstraintsOpinionsofSMEsTimeandmoneyconstraints54SimulationModelingandAnalysis–Chapter1–Basic