UntitledFR11doc文档格式.docx

UntitledFR11doc文档格式.docx

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aInstituteofIntelligentEngineeringandMathematics,LiaoningTechnicalUniversity,FuxinCity,

LiaoningProvincef123000，China;

bCentreofNewEnergySystems,DeptofElectrical,ElectronicandComputerEngineering,Universityof

Pretoria,Pretoria0002,SouthAfrica

（Received00Month20XX;

finalversionreceived00Month20XX）

Inthepaper,atypicalcoaltradeprocessisdescribedandmodelled,whereonelogisticsenterprisewithblendingequipmentsliesinthecoreandtwotypesofcommoncontractsareelucidatedtodefineconstraints.Amixed-integermodelisbuiltandfeaturedbyaddressingcontractviolation,blendingoperation,realtimepriceinformationandarbitrarilydistributedstochasticdemands.Todealwiththestochasticdemands,probabilisticconstraintsareformed.Accordingly,stochasticmodelpredictivecontrol（SM-PC）strategywithbothrecedinghorizonanddecreasinghorizonformulationsisdevelopedtohandletheprobabilisticconstraintsandexploitthevalueofnewestpriceinformation.Bysolvingaseriesofmixed-integerlinearprograms,optimalcoaltradedecisionsforthelogisticsenterprisecanbeobtained,includingprocurementdecision，sellingdecisionandoperationaldecisionoftheblendingequipments.

Thoroughsimulationexperimentsarecarriedoutandcomparedunderthreedifferentstrategies,whichinterprettheeffectivenessoftheproposedstrategy.

Keywords:

coaltradedecisions;

stochasticdemands;

blendingoperation;

stochasticmodelpredictivecontrol

1.Introduction

Coalisonemajorsourcefortotalenergysupplyintheworld.Thepercentageofcoalamongallfuelsis19.5%in2012，followingafteroilwiththepercentageof36.1%（accordingtodatafromInternationalEnergyAgency;

IEA2013）.Andcoaltakesupthelargestpartinelectricitygeneration,theratioofwhichis41.3%in2011.Coaltradebothintheinternationalmarketanddomesticmarketisveryactive.Forexample,coalproductionandnetimportsforChinareadied3,549Mt（milliontonnes）and278Mtrespectivelyin2012.

Coaltradeprocessusuallyinvolvesthreesides,namelycoalsuppliers,logisticsenterprisesandcoaJconsumers,amongwhichtheroleoflogisticsenterprisesisbecomingmoreandmorepredominant.Generally,thelogisticsenterpriseisinchargeofsearchingfordemandsfromdifferentconsumerssuchaspowercompanies,cementcompaniesandsteelcompanies,andthenformulatingasetofcoaltradedecisions,includingprocuringcoalsfromsuppliers,transportingcoalsandblendingdifferenttypesofcoalstorenderthemsuitablefordifferentplants.Coalblendingisdesiredbymoreconsumersatthecurrentmoment,sincetherearemoreandmorestringentenvironmentalregulationswhichrequirethatcontentsofsomeelements/attributesofcoalsshouldbewithincertainupperorlowerlimits.Moreover,differentburningplantsmayhavedifferentpreferencesoncoalqualities.Forexample,thesulfuroxidecontentofcoalstoentertheburningplantsofpowercompaniescannotbegreaterthan0.7%acrossGuangdongProvinceofChinasince2014.Tomeetthisregulation,differentcoalswithsulfuroxidecontentaboveandbelow0.7%canbe

•CorrfapomjiiigautlidEmail:

chengqifeng^t«

mixedtogetherthroughtheblendingequipments,otherwisetoonlyconsidercoalswithsulfuroxidecontentbelow0.7%canbeveryexpensiveduetoinsufficientsupplyinthemarket.Nowadays,manyconsumersonlyproposetheirrequirementstothelogisticsenterpriseandallthejobsareduetotheresponsibilityofthelogisticsenterprise.Thus,blendingcapabilityisonekeyrolethatthelogisticsenterprisecanplay.Thispaperwillfocusonthemodellingandoptimizationforatypicalcoaltradeproblem,whereonelogisticsenterpriseequippedwithblendingfacilitiesliesinthecoreofthetradeprocess.Ascanbeexpected,thisresearchwillexploremoreprofitsforthelogisticsenterprise.Moresignificantly,optimizingcoaltradedecisionscanbringmanybenefitstothewholetradesystem,suchasincreasingthecirculationandblendingofcoalstomeetvariousdemands,reducingcostsforconsumers,storingcoalsasabuffertodealwithpossibleemergencieswhichmaythreatenthesupplymarket.

Littleresearchhasbeendoneonthistypeofcoaltradeoptimization,whichincorporatescontractviolation,blendingoperation,newestinformationonpriceforecastandstochasticnatureofdemands.Inthispaper,weextendpreviousresearchforthefollowingfouraspects:

1）Theresearchiscarriedoutfromtheviewofthelogisticsenterprise,whichlocatesatthecoreofcoaltradeprocess.Asstatedabove,shapingoptimaldecisionswillmakethewholetradeprocessmoreefficient.2）Thestochasticpropertiesofdemandsinthefuturearetakenintoaccountexplicitly,whereaseriesofprobabilisticconstraintsareformulated.3）Theproblemofsatisfactionorbreachofthetradecontractisaddressedinthemodellingandoptimization.4）Stochasticmodelpredictivecontrolstrategy,withbothrecedinghorizonanddecreasinghorizonformulations,isdevisedtoachieveoptimalperformance.

Thepaperisproceededasfollows.Relatedliteratureisreviewedin§

2.Thedetailsofmodelling,

1.e.,assumptions,objectiveformulationandvariousconstraints,arepresentedin§

3.In§

4,stochasticmodelpredictivecontrolstrategyisdeveloped.Anillustrativeexampleisstudiedthoroughlyin§

5andweconcludethepaperin§

6.

2.LiteratureReview

Thisresearchisinconnectionwiththreetypesofproblemsinexistingliteratures,i.e.,coallogisticsoptimization,commoditytradeproblemandsupplychainoptimization.Theconnectionsanddifferencesaresetforthbelow.

2.1CoalLogisticsOptimization

Coalblindinganddistributionproblemhasdrawnalotofattentions,whichcanbefoundin（SheraliandPuri1993;

ShihandFrey1995;

Cao,Lin,andYan2006;

Liu2008;

Yabin2010;

Yucekaya2013,andreferencestherein）.CoalblendingcostisminimisedinShihandFrey（1995）byincorporatingtheuncertaintyofcoalelements/attributes.AtotalcostofthelogisticssystemistakenintoaccountinCao,Lin,andYan（2006）,includingrailwaytransportationcost,procurementcost,orderingcostandholdingcost.TheblendingissueistreatedaswellinCao,Lin,andYan（2006）,however,itdoesnottakeintoaccountthestochasticvariationofbothpriceanddemands.InLiu（2008）,theblendingandinter-modaltransportationproblemissufficientlyaddressed,yetneitherdemandvariationnorpriceupdateisaccountedfor.ThepricechangeforprocurementandtransportationanddemandchangehavebeenaccommodatedintheoptimizationproblemofYabin（2010）,whileitassumesthatbothpricechangeanddemandchangearefixed,whichisnotrealisticbyneglectingthestochasticnatureofthesechanges.Amulti-objectiveoptimization,consideringmultiplesuppliers,multipleroutes,multipleproductsandthecoalqualityconstraints,isformulatedinYucekaya（2013）,yetwithouttreatmentofthepriceanddemandvariation.

Ourresearchdifferentiatessignificantlyfromtheliteraturesaboveintwopoints.Firstly,wenotonlyconsiderthequalityrequirementsbyblendingdifferenttypesofcoals,butmorespecifically,weoptimizetheoperationaldecisionsofblendingequipmentsforthelogisticsenterprise.Tothebestknowledgeofus,thisproblemhasnotbeenhandledbefore.Secondly,wemakeuseoftheinformationonthestochasticdistributionsofdemandsexplicitly,whereprobabilisticconstraintsareposedandtreated.Realtimeinformationonpriceforecastisalsoincorporatedinourmodel,whichisfacilitatedbythestochasticmodelpredictivecontrolstrategy.

2.2CommodityTradeProblem

Thereareabundantliteraturesoncommoditytradeproblem,suchasBerlingandMartmez-deAl-beniz（2011）;

Xie,Park,andZheng（2013）,andtheirreferences.InBerlingandMartfnez-deAlbania（2011）,aninventorycontrolmodelforspotmarketprocurementisdevisedbytakingbothpurchasepriceanddemandtobestochastic.Itinvestigatesaone-factorpricemodel,andassumesthatthearrivalprocessofdemandisPoisson,whichisstochasticandlimited.Thereplenishmentcapacityisregardedasinfinite.AcrudeoilprocurementstrategyforChineseoilrefineriesisdevelopedinXie,Park,andZheng（2013）,withdeterministicdemandsandindependentuncertainpurchaseprices.ABayesianlearningmethodisutilizedtoactivelyassimilaterealtimepriceinformation.Inthecoaltradeprocesswiththelogisticsenterprise,contractsgenerallyexisttoensuredemandpredictionsmoreaccurateandtheprocurementplanningmorerealistic,thusneitherreplenishmentnordemandcanbeinfinite.Moreover,therearephysicalconstraintsonthestoragecapacityandblendingcapacity,andthetradeprocessconcernsblendingofmultipleproducts（coals）,whichbothcomplicatetheproblem.Modelpredictivecontrolisemployedinourstudytomakeuseofthenewestinformationregardingpriceanddemand,whichhasacertaindegreeofinherentrobustnessagainstexternaldisturbances,modeluncertaintyandmodelmismatch（Maciejowski2002;

vanStaden,Zhang,andXia20li）.

2.3SupplyChainOptimization

Variouscontrolstrategieshavebeensuccessfullyappliedinsupplychainoptimizationproblem,e.g.,Perea-L6pez,Ydstie,andGrossmann（2003）;

SeferlisandGiannelos（2004）;

Alessandri,Gag-gero,andTonelli（2011）;

Sarimveisetal.（2008）.InPerea-Lopez,Ydstie,andGrossmann（2003）;

Alessandri,Gaggero,andTonelli（2011）,themodelpredictiveco