logwareSELECTED COMPUTER PROGRAMS FOR PLANNING.docx
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logwareSELECTED COMPUTER PROGRAMS FOR PLANNING.docx
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logwareSELECTEDCOMPUTERPROGRAMSFORPLANNING
SELECTEDCOMPUTERPROGRAMS
FORLOGISTICS/SUPPLYCHAINPLANNING
Version5.0
RonaldH.Ballou
WeatherheadSchoolofManagement
CaseWesternReserveUniversity
(C)Copyright1992-2004RonaldH.BallouAllrightsreserved
SELECTEDCOMPUTERPROGRAMS
FORLOGISTICS/SUPPYCHAINPLANNING
LOGWAREisacollectionofselectedsoftwareprogramsthatisusefulforanalyzingavarietyoflogistics/supplychainproblemsandcasestudies.Itcontainsthefollowingmodules.
Module
Page
FORECASTForecaststimeseriesdatabymeansofexponentialsmoothingandtimeseriesdecompositionmethods
5
ROUTEDeterminestheshortestpaththroughanetworkofroutes
9
ROUTESEQDeterminesthebestsequencetovisitstopsonaroute
13
ROUTERDevelopsroutesandschedulesformultipletrucksservingmultiplestops
15
INPOLFindsoptimalinventoryorderingpoliciesbasedoneconomicorderquantityprinciples
24
COGFindsthelocationofasinglefacilitybytheexactcenter-of-gravitymethod
33
MULTICOGLocatesaselectednumberoffacilitiesbytheexactcenter-of-gravitymethod
37
PMEDLocatesaselectednumberoffacilitiesbytheP-medianmethod
41
WARELOCAAwarehouselocationprogramforspecificallyanalyzingtheUsemoreSoapCompanycasestudy
45
LAYOUTPositionsproductsinwarehousesandotherfacilities
47
MILESComputesapproximatedistancebetweentwopointsusinglatitude-longitudeorlinear-gridcoordinatepoints
49
TRANLPSolvesthetransportationmethodoflinearprogramming
51
LNPROGSolvesgenerallinearprogrammingproblemsbymeansofthesimplexmethod
53
MIPROGSolvesthemixedintegerlinearprogrammingproblembymeansofbranchandbound
55
MULREGFindslinearregressionequationsbymeansofthestepwiseprocedureofregression/correlationanalysis
57
SCSIMSimulatestheflowofaproductthroughfiveechelonsofasupplychannel
62
Eachmoduleisselectedfromthefollowingmasterscreenbyclickingontheappropriatebutton.
HARDWAREREQUIREMENTS
LOGWAREisdesignedformicrocomputersoperatingunderWINDOWS98,NT,2000,orXP.Atleast16MBofRAMshouldbeinstalled.Harddrivespaceofatleast10MBshouldbeavailable.Acolormonitorcapableofproducingatleast640x480pixelsresolutionisneeded,although800x600isbetterand1024x768ispreferred.Resolutionsgreaterthan1024x768pixelsarenotsupported.Alaserprinterispreferred.Amouseisneeded.A3½floppydriveand/oracompactdiskreaderareneeded.
INSTALLINGTHESOFTWAREONAHARDDRIVE
Placetheprogramcompactdisksintheappropriatedrives.InWINDOWS,clickontheStartbuttonandthenselecttheRunoptionfrompop-upmenu.Type“X:
Setup.exe”(“X”beingtheletterdesignatedforyourCDdrive).TheprogrammayalsobeinstalledwithWindows’Start,Settings,ControlPanel,Add/RemovePrograms,Installoption.Changethesubdirectoryunderwhichtheprogramwillbeinstalledifthedefaultsubdirectoryisnotdesired.
RUNNINGTHEPROGRAMS
Aftertheprogramisinstalled,clickontheStartbuttonandselectPrograms.ChoosetheLogwareicontoactivatetheprogram.Clickonthedesiredprogrammodule.AshortcuticonontheDesktopmayalsobecreated.
EDITINGTHEDATA
Inthosemoduleswhereascreendataeditorispresent,thefirstactionistoopenadatafilebyclickingonthemodule’sStartbutton.Ifafileisnamedthatisnotinthecurrentlistoffiles,adatashellwillbecreatedintowhichanewproblemmaybeentered.Theuseoftheeditorissimpleandtransparentwithalittlepractice;however,afewcommentsaboutitsusemayhelptogetstarted.
PresstheInskeytostartanewlineofdatainamatrix.Thenormalactionistoinsertatextrowattheendofthematrix.TheAddbuttonmayalsobepressed.Thiswillallowarowtobeaddedattheendofthematrixaswellaswithinthematrix.Positionthecursorinthematrixrowwheretherowistobeadded.
PressingtheEsckeyclearsamatrixcell.
∙PressingtheDeletebuttondeletestherowinamatrixhighlightedbythecurrentcursorposition.
∙IfColumnarithmeticistobeused,highlightthematrixcolumnonwhichtheactionistoapply.
Alternatively,thedataforeachmoduleexceptSCSIMmaybecreatedandeditedwiththeuseofExcel.ItisexpectedthattheuserhasabasicknowledgeofExceluse.
COPYINGTHEINSTRUCTIONSANDTHESOFTWARE
Thissoftwareandtheassociatedinstructionsmaybecopiedaslongastheyareusedforeducationalpurposes.Allcopiedmaterialsmustdisplaythefollowingcopyrightnotices.
Copyright1992-2004RonaldH.BallouAllrightsreserved.
RonaldH.Ballouoffersthissoftwareforeducationalpurposesonlyanddoesnotwarrantthesoftwaretobefitforanyparticularapplication.TheuseragreestoreleaseRonaldH.Balloufromallliabilities,expenses,claims,actions,and/ordamagesofanykindarisingdirectlyorindirectlyoutoftheuseofthesecomputerprograms,theperformanceornonperformanceofsuchcomputerprograms,andthebreachofanyexpressedorimpliedwarrantiesarisinginconnectionwiththeiruse.Iftheseconditionsarenotacceptable,thesoftwareshouldbereturnedtoRonaldH.Ballou.
ProfessorRonaldH.Ballou
WeatherheadSchoolofManagement
CaseWesternReserveUniversity
Cleveland,OH44106USA
Tel:
(216)368-3808
Fax:
(216)368-6250
E-mail:
Ronald.Ballou@Weatherhead.CWRU.edu
Uptodateinformationaboutthesoftwaremaybefoundatwww.PrenH
INSTRUCTIONSFOREXPONENTIALSMOOTHING
ANDTIMESERIESDECOMPOSITIONFORECASTING
FORECAST
FORECASTiscomputersoftwarethatforecastsfromtimeseriesdatabymeansofexponentialsmoothingand/ortimeseriesdecompositionmethods.Inlogistics/SC,suchtimeseriesmaybeproductsales,leadtimes,pricespaidforgoods,orshipments.Thephilosophyoftimeseriesforecastingistoprojectanhistoricalpatternofthedataovertime,and,ifpresent,accountfortrendandseasonality.Exponentialsmoothingisamovingaverageapproachthatprojectstheaverageofthemostrecentdataandadaptstheforecasttochangingdataastheyoccur.Ontheotherhand,thetimeseriesdecompositionapproachrecognizesthatmajorreasonsforvariationindataovertimeareduetotrendandseasonalcomponents.Eachoftheseisestimatedandcombinedtoproduceaforecast.ForbackgroundinformationontheforecastmodelsusedinFORECAST,seeChapter8oftheBusinessLogistics/SupplyChainManagement5etextbook.
TorunFORECAST,selecttheappropriatemodulefromtheLOGWAREmastermenu.Openanexistingfileorselectanewone.Prepareorchangethedatabase.Selecttheappropriatemodeltype,whichmaybeeithersomeformofanexponentialmodel(Levelonly,Level-Trend,etc.)orthetimeseriesdecompositionmodel.ClickonSolvetogenerateaforecast.
INPUT
Theinputtobothforecastingmodulesconsistsofthetime-orderedseriesofdata,rankedfromthemosthistorictothemostrecentobservations,andvariousparametervaluesthatguidetheexecutionofthemodels.Thedimensionsofthemodelsallowobservationsforupto200periodsandaforecastofupto50periods.Bothmodeltypesrunfromthesamedatabasealthoughsomeoftheparametersarenotusedinthetimeseriesdecompositionmodel.
ParametersandLabels
Thisportionofthescreensetstheparametersforboththeexponentialsmoothingandtimeseriesdecompositionmodels.Theseguidetheoverallactionofthemodels.Considereachelementonthisscreen.
Problemlabel.Thisisalabelgiventotheproblemyouaresolving.WARNING:
Donotusecommas(,)ordoublequotationmarks(")inthelabelsincethiswillcauseanerrorinreadingthedatafile.
Numberofdatapoints.Specifythenumberofdataperiodsinthetimeseries.Upto200pointsareallowed.Besurethatthenumberofpointsspecifiedherematchesthenumberofdatapointsactuallyenteredinthetimeseries.
Initializationperiod.Theinitializationperiodisthenumberoftheoldestdatapointsusedtodeterminestartingvaluesfortheexponentialsmoothingmodel.Aminimumof3periodsofdatashouldbedeclaredforthispurpose.Ifaseasonalmodelistobeused,atleastthenumberofperiodsinonefullseasonalcyclemustbespecified.
Errorstatistics.Thenumberofdataperiodsneededtocomputeforecasterrorstatisticsisreferredtoasthevalidationperiod.Theseerrorstatisticsarethemeanabsolutedeviation(MAD),thebias(BIAS),andtherootmeansquareerror(RMSE).ThevalidationperiodisthelastNperiodsofdata.Enoughdatapointsshouldbeusedfromthisvalidationperiodtostrikeareasonableaverageforthesestatistics.
MADisdefinedastheaverageoftheabsolutedifferencesbetweentheactualvaluesandtheforecastvaluesforthevalidationperiod.BIASistheaverageofthedifferencesbetweenactualandforecastvaluesforthevalidationperiod.RMSEissquarerootoftheaverageofthesquareddifferencesbetweentheactualandtheforecastvaluesforthevalidationperiod.
Modeltype.Selectingthemodeltypereferstotheexponentialsmoothingmodelorthetimeseriesdecompositionmodel.Therearefourvariationsoftheexponentialsmoothingmodelforbestrepresentingthecharacterofthetimeseries.ThesearetheLevelonly,Level-Trend,Level-Seasonal,andLevel-Trend-Seasonal.Selectthetypethatbestrepresentsthedata.Alternately,selectthetimeseriesdecompositionmodel.Smoothingconstantsearch.Whenoneoftheformsoftheexponentialmodelisselected,indicatewhetherasearchforthesmoothingconstantsistobeperformedusingFORECAST.Ifnot,thesmoothingconstantsforthemodeltypeselectedmustbespecified.
IfFORECASTistosearch
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