建筑外文文獻(xiàn)及翻譯

建筑大學(xué)畢業(yè)設(shè)計外文文獻(xiàn)及譯文-外文原文StudyonHumanResourceAllocationinMulti-ProjectBasedonthePriorityandtheCostofProjectsLinJingjing,ZhouGuohuaSchoolofEconomicsandmanagement,SouthwestJiaotongUniversity,610031,ChinaAbstractThispaperputforwardtheaffectingfactorsofproject’spriority.whichisintroducedintoamulti-objectiveoptimizationmodelforhumanresourceallocationinmulti-projectenvironment.Theobjectivesofthemodelweretheminimumcostlossduetothedelayofthetimelimitoftheprojectsandtheminimumdelayoftheprojectwiththehighestpriority.ThenaGeneticAlgorithmtosolvethemodelwasintroduced.Finally,anumericalexamplewasusedtotestifythefeasibilityofthemodelandthealgorithm.IndexTerms—GeneticAlgorithm,HumanResourceAllocation,Multi-project’sproject’spriority.INTRODUCTIONMoreandmoreenterprisesarefacingthechallengeofmulti-projectmanagement,whichhasbeenthefocusamongresearchesonprojectmanagement.Inmulti-projectenvironment,thesharearecompetitionofresourcessuchascapital,timeandhumanresourcesoftenoccur.Therefore,it’scriticaltoscheduleprojectsinordertosatisfythedifferentresourcedemandsandtoshortentheprojects’durationtimewithresourcesconstrained,asin[1].Formanyenterprises,thehumanresourcesarethemostpreciousasset.Soenterprisesshouldreasonablyandeffectivelyallocateeachresource,especiallythehumanresource,inordertoshortenthetimeandcostofprojectsandtoincreasethebenefits.Someliteratureshavediscussedtheresourceallocationprobleminmulti-projectenvironmentwithresourcesconstrained.Reference[1]designedaniterativealgorithmandproposedamathematicalmodeloftheresource-constrainedmulti-projectscheduling.Basedonworkbreakdownstructure(WBS)andDantzig-Wolfedecompositionmethod,afeasiblemulti-projectplanningmethodwasillustrated,asin[2].References[3,4]discussedtheresource-constrainedprojectschedulingbasedonBranchDelimitationmethod.Reference[5]putforwardtheframeworkofhumanresourceallocationinmulti-projectinLong-term,medium-termandshort-termaswellasresearchanddevelopment(R&D)environment.BasedonGPSSlanguage,simulationmodelofresourcesallocationwasbuilttogettheproject’sdurationtimeandresourcesdistribution,asin[6].Reference[7]solvedtheengineeringproject’sresourcesoptimizationproblemusingGeneticAlgorithms.Theseliteraturesreasonablyoptimizedresourcesallocationinmulti-project,butallhadthesameprerequisitethattheproject’simportanceisthesametoeachother.Thispaperwillanalyzetheeffectsofproject’spriorityonhumanresourceallocation,whichistobeintroducedintoamathematicalmodel;finally,aGeneticAlgorithmisusedtosolvethemodel.EFFECTSOFPROJECTSPRIORITYONHUMANRESOUCEALLOCATIONANDTHEAFFECTINGFACTORSOFPROJECT’SPRIORITYResourcesharingisoneofthemaincharacteristicsofmulti-projectmanagement.Theallocationofsharedresourcesrelatestotheefficiencyandrationalityoftheuseofresources.Whenresourceconflictoccurs,theresourcedemandoftheprojectwithhighestpriorityshouldbesatisfiedfirst.Onlyafterthat,cantheprojectswithlowerprioritybeconsidered.Basedontheideaofprojectclassificationmanagement,thispaperclassifiestheaffectingfactorsofproject’spriorityintothreecategories,astheproject’sbenefits,thecomplexityofprojectmanagementandtechnology,andthestrategicinfluenceontheenterprise’sfuturedevelopment.Thepriorityweightoftheprojectisthefunctionoftheabovethreecategories,asshownin(1).W=f(I,c,s…)(1)Wherewreferstoproject’spriorityweight;Ireferstothebenefitsoftheproject;creferstothecomplexityoftheproject,includingthetechnologyandmanagement;sreferstotheinfluenceoftheprojectonenterprise.Thebiggerthevaluesofthethreecategories,thehigherthepriorityis.HUMANRESOURCEALLOCATIONMODELINMULTI-PROJECTallocatedtoprojectsIactually,withtheequationRi*=existing.DuetotheresourcecompetitiontheresourcedemandsofprojectswithhigherPrioritiesmaybeguarantee,whilethoseprojectswithlowerprioritiesmaynotbefullyguaranteed.Inthissituation,thedecreaseoftheresourcesupplywillleadtotheincreaseofthedurationtimeofactivitiesandtheproject,whiletheworkloadisfixed.OptimizationModelBasedontheabovehypotheses,theresourceallocationmodelinmulti-projectenvironmentcanbeestablished.Here,theoptimizationmodelis:Fi=minZi=min=min(2)=min=minZ2=min=min(3)Wherewj=max(wi),()(4)Subjectto:0=R(5)Themodelisamulti-objectiveone.Thetwoobjectivefunctionsarerespectivelytominimizethetotalcostloss,whichistoconformtotheeconomictarget,andtoshortenthetimedelayoftheprojectwithhighestpriority.Thefirstobjectivefunctioncanonlyoptimizetheapparenteconomiccost;thereforethesecondobjectivefunctionwillhelptomakeupthislimitation.Fortheprojectwithhighestpriority,timedelaywilldamagenotonlytheeconomicbenefits,butalsothestrategyandtheprestigeoftheenterprise.Thereforeweshouldguaranteethatthemostimportantprojectbefinishedontimeoraheadofschedule.SOLUTIONTOTHEMULTI-OBJECTIVEMODELUSINGGENETICALGORITHMThemulti-objectiveoptimizationproblemisquitecommon.Generally,eachobjectiveshouldbeoptimizedinordertogetthecomprehensiveobjectiveoptimized.Thereforetheweightofeachsub-objectiveshouldbeconsidered.Reference[8]proposedanimprovedantcolonyalgorithmtosolvethisproblem.Supposedthattheweightsofthetwooptimizingobjectivesareαandβ,whereα+β=1.ThenthecomprehensivegoalisF*,whereF*=αF1+βF2.ThePrincipleofGeneticAlgorithmGeneticAlgorithmrootsfromtheconceptsofnaturalselectionandgenetics.It’sarandomsearchtechniqueforglobaloptimizationinacomplexsearchspace.Becauseoftheparallelnatureandlessrestrictions,ithasthekeyfeaturesofgreatcurrency,fastconvergenceandeasycalculation.Meanwhile,itssearchscopeisnotlimited,soit’saneffectivemethodtosolvetheresourcebalancingproblem,asin[9].ThemainstepsofGAinthispaperareasfollow:EncodingAnintegerstringisshort,directandefficient.Accordingtothecharacteristicsofthemodel,thehumanresourcecanbeassignedtobeacodeobject.Thestringlengthequalstothetotalnumberofhumanresourcesallocated.ChoosingthefitnessfunctionThispaperchoosetheobjectivefunctionasthefoundationoffitnessfunction.Toratethevaluesoftheobjectivefunction,thefitnessofthen-thindividualis1/。GeneticoperationIt’sthecoreofGA.Thisprocessincludesthreebasicoperators:selectionoperator,crossoveroperator,andmutationoperation.Selectionoperationistoselectthegoodindividualsamongthegroup.Theprobabilityofastringtobeselectedasaparentisproportionaltoitsfitness.Thehigherthestring’sfitnessis,thegreatertheprobabilityofthestringtobeselectedasaparentwillbe.CrossoveroperatorTheso-calledcrossoveristhatthepatenchromosomesexchangesomegenestoyieldtwooffspringstringsinsomerule.Wecanuseuniformcrossover,thatthetwochromosomesexchangethegenesonthesamepositionswiththesamecrossoverprobabilitytoyieldtwonewindividuals.MutationoperatorMutationaddstothediversityofapopulationandtherebyincreasesthelikelihoodthatthealgorithmwillgenerateindividualswithbetterfitnessvalues.ThemutationoperatordeterminesthesearchabilityofGA,maintainthediversityofapopulation,andavoidtheprematurity.Thereareseveralmutationisquiteeasy.StandardfortheterminalofGAWithouthumancontrol,theevolutionprocessofthealgorithmwillneverend.Thepopulationsizeaffectsthefinalresultandtheoperationspeed.Ifthesizeisgreater,thediversityofthepopulationcanbeadded,andthebestresultcanbeobtainedeasier.However,theefficiencyisreduced.Recently,inmostGAprogress,thebiggestevolvementalgebraisdeterminedbyhuman-beingstocontrolthecoursethealgorithm.NUMERICALEXAMPLEWeuseanumericalexampletoillustratetheeffectivenessofGeneticAlgorithm.Assumethattherearethreeprojectswiththesamenetwork,andthepriorityweightshavebeenputforward.Thereisonlyonecriticalpathineachproject.ThedatawehaveknownareshowninTable1.Table1DataoftheThreeProjectsProjectPriorityweightwtECostloss(humanyuan/day)Workload(person*day)10.421010010020.3181508030.271280120ThestepsofGeneticAlgorithmtosolvethemodelareasfollow:Step1:Anintegerstringisadopted.Encodewith[0,1,2]fortherearethreeprojects.Thelengthofthechromosomeis16,thetotalnumberofhumanresourcetobeallocated.Step2:Theinitialpopulationsizeis50.Step3:Doinggeneticoperation.AdoptRouletteWheelandElitisttactictodeterminedselectionoperator.Theoffspringcanbeyieldedbyuniformcross-over.Themutationoperatorcanbedeterminedbyuniformmutation.Weassumethatthemutationprobabilityequalto0.001.Step4:Adoptthemaximumpopulationsizeis100whenterminated.Afterthecomputersimulation,wecanobtainthePare-toresultswithdifferentimportanceweightsofthetwoobjectivefunctions,asshowninTable2:Table2TheSolutionResultoftheModelR1*R2*R3*F1(HundredYuan)F2(Day)α=1,β=0655911.22.8α=0.7,β=0.3754940.81.8α=0.4,β=0.68441051.81.05α=0.1,β=0.910331472.80Fromtable2wecanlearnthat,whenαandβchange,theresultisdifferent.HoweverwecanobtainaseriesofParetoresults.CONCLUSIONHumanresourceallocationinmulti-projectenvironmentisacomplicatedproblem.Thispaperanalyzestheimportanceofproject’spriorityinresourceallocationandestablishesahumanresourceallocationmodelbasedonpriorityandcostofprojects.Finally,geneticAlgorithmisadoptedtosolvethemodel.Duringtheconstructionprocessoftheallocationmodel,wehaveputforwardsomehypothesesinordertosimplifytheproblem.However,whentheenterprisespracticallyallocatetheresources,heywillfacemorecomplexity,whichisthefocusofourfuturestudy.中文翻譯：在項目優(yōu)先權(quán)和成本的基礎(chǔ)上對多項目中人力資源配置的研究林晶晶，周國華中國西南交通大學(xué)經(jīng)濟和管理學(xué)院，610031摘要本文提出項目優(yōu)先次序的影響因素，為多項目環(huán)境配置人力資源引入一個多目標(biāo)優(yōu)化模型。這一模型的目標(biāo)是使得由于項目時間限制的延誤損失的成本最低和具有最高優(yōu)先順序項目的延遲最小。然后用遺傳算法求解該模型。最后，用一個數(shù)值例子證明該模型和算法的可行性。關(guān)鍵字遺傳算法;人力資源配置;多項目、項目的優(yōu)先權(quán);1、引言越來越多的企業(yè)面臨的挑戰(zhàn)是多項目管理，這已經(jīng)成為項目管理研究的焦點。多項目環(huán)境中，諸如資金，時間和人力等資源的共享和競爭經(jīng)常發(fā)生。因此合理安排項目的進(jìn)度，以滿足不同資源的需求并縮短項目造成的資源約束。對于許多企業(yè)來說，人力資源是最寶貴的資產(chǎn)。所以企業(yè)應(yīng)合理有效分配每個資源，尤其是人力資源，用以縮短時間減少項目的成本和增加效益。一些文獻(xiàn)中曾討論的存在資源約束的多項目環(huán)境中資源分配問題。設(shè)計一個迭代算法，并提出了資源約束的多項目調(diào)度的數(shù)學(xué)模型?；诠ぷ鞣纸饨Y(jié)構(gòu)（wbs）和dantzig-wolf的分解方法，人們曾演示過一個可行的多項目規(guī)劃方法。討論基于分支定界的方法的資源受限項目的調(diào)度。提出在長期、中期和短期的多項目及研究和開發(fā)（R＆D）環(huán)境中人力資源配置框架。在gpss語言的基礎(chǔ)上，為了獲得該項目的持續(xù)時間和資源的分配而建立仿真模型的資源配置。用遺傳算法解決了工程項目的資源優(yōu)化問題。這些文獻(xiàn)雖然合理優(yōu)化了多項目的資源配置，但它們都有相同的先決條件即該項目的重要性是一樣。本文將引進(jìn)數(shù)學(xué)模型用以分析項目優(yōu)先權(quán)在人力資源配置中的作用。最后，用遺傳算法求解這一模型。2.項目優(yōu)先權(quán)對人的資源分配的作用和影響項目優(yōu)先權(quán)的因素資源共享是是多項目管理一個主要特點。共享資源的分配涉及到資源使用的效率和合理性，當(dāng)資源發(fā)生沖突時，應(yīng)該首先滿足最高優(yōu)先權(quán)項目的資源的需求。在此之后，較低優(yōu)先權(quán)的項目才予以考慮?；陧椖糠诸惞芾淼乃枷?，本文將歸類項目的優(yōu)先次序的影響因素分為三類。正如項目的利潤一樣，復(fù)雜的項目管理和技術(shù)以及戰(zhàn)略都影響著企業(yè)的未來發(fā)展。優(yōu)先權(quán)的重量級取決于該項目上述三大類因素。公式為：W=f(I,c,s…)(1)其中w是指項目的優(yōu)先權(quán)重；i指該項目的利潤，;c指項目中技術(shù)和管理的復(fù)雜性;s指該項目對企業(yè)的影響。三類因素的價值越大，其優(yōu)先級越高。3、在多項目環(huán)境下的人力資源分配模型。3.1、問題描述根據(jù)約束理論，企業(yè)應(yīng)嚴(yán)格區(qū)分瓶頸資源和非瓶頸資源來解決瓶頸資源的約束問題。本文將著力研究被分配在多項目中有限且關(guān)鍵的人力資源，而這些多項目都有明確的期限和時代優(yōu)先權(quán)。為了簡化問題，我們假設(shè)存在平行的幾個項目和一個共享的資源庫，且企業(yè)的運作只涉及一種重要的人力資源。關(guān)鍵人力資源的供應(yīng)是有限的，在一定期限內(nèi)是不能通過雇用或憑借任何其他方式獲得的。當(dāng)資源之間的沖突在并行項目中發(fā)生時，我們可能會根據(jù)項目的優(yōu)先次序分配人力資源。本文不考慮非關(guān)鍵獨立的人力資源的配置問題，這是假定這些獨立的資源可以滿足每個項目的需求。工程項目通常在一些關(guān)鍵鏈需要大量的關(guān)鍵技術(shù)熟練的人力資源，而這些資源是由其他人力資源所不能取代。在某時期內(nèi)，當(dāng)項目的幾個關(guān)鍵環(huán)節(jié)同時需要同一種關(guān)鍵性人力資源時就會發(fā)生資源的沖突和競爭。本文還假設(shè)認(rèn)為，各個項目已經(jīng)建立相應(yīng)的網(wǎng)絡(luò)規(guī)劃，并且每個項目的資源需求的高峰期已得到優(yōu)化。關(guān)鍵環(huán)節(jié)的延誤將會影響整個項目的持續(xù)時間。3.2模型假設(shè)

以下假說幫助我們建立一個數(shù)學(xué)模型：(1)介入多項目的資源分配問題的相互獨立項目的數(shù)量是N。每個項目Q用表示，而i=1,2，…N。(2)確定了多項目優(yōu)先權(quán)重量，各自是w1，w2…wn。(3)重要人力資源的總數(shù)是R，用rk代表每個人，而k=1,2，…，R(4)ki=(5)幾個項目共用的資源從時間ts開始。tEi是人力資源的需求可以得到滿足的前提下項目i的預(yù)計持續(xù)時間，項目i在ts后需要關(guān)鍵資源來完成某些任務(wù)。(6)根據(jù)合同，如果該項目延誤則由延誤對項目i造成的每日成本損失為△Ci。根據(jù)該項目的重要性，工程延誤后不但會造成成本的損失，而且還會損害企業(yè)的威望和地位。（而潛在的成本是難以量化的，這在本文中暫時不做考慮）。(7)從假說（5），我們可以知道在時間ts后，項目i真正持續(xù)時間和預(yù)期持續(xù)時間的時間差距為△ti,(△ti=tAi-tEi)。由于存在著資源的競爭，時間的差距必然是一個正數(shù)。(8)根據(jù)假說(6)和(7)，項目i總的成本損失是Ci(Ci=△ti*△Ci)。(9)活動持續(xù)時間可以用活動的工作量除以資源的數(shù)量表達(dá)，用下面的表達(dá)式表示為tAi=ηi/R*i。在這個表達(dá)式中，ηi指在某一時期項目i的工作量，它應(yīng)該是固定和預(yù)先確定的。R*i是指在項目經(jīng)理對項目的規(guī)劃階段被實際上分配給項目i中的關(guān)鍵人力資源的數(shù)量。于是存在方程Ri*=。由于資源的競爭，具有較高優(yōu)先權(quán)項目的資源需求可能得到保障，而那些較低的優(yōu)先權(quán)的項目可能無法得到充分保障。在這種情況下當(dāng)工作量是固定的，減少了資源的供應(yīng)將導(dǎo)致活動和項目持續(xù)時間的增加。3.3優(yōu)化模型基于上述的假設(shè)確立多項目環(huán)境的資源分配模型。這里的優(yōu)化模型表示為：Fi=minZi=min=min(2)=min=minZ2=min=min(3)Wherewj=max(wi),()(4)Subjectto:0=R(5)該模型是一個多目標(biāo)形式的。這兩個目標(biāo)函數(shù)一個是為符合經(jīng)濟目標(biāo)以盡量減少總的成本損失，另一個是以縮短有最高優(yōu)先權(quán)項目的延遲時間。由于第一個目標(biāo)函數(shù)只能優(yōu)化明顯的經(jīng)濟成本，因此第二個目標(biāo)函數(shù)將有助于彌補此限制。對于有最高優(yōu)先權(quán)的項目，時間延遲將會損害的不僅有經(jīng)濟利益，而且也會損害企業(yè)的策略和威望。因此，我們應(yīng)保證最重要的項目應(yīng)按時完成或提前完成。4、用遺傳算法求解多目標(biāo)模型4.1多目標(biāo)優(yōu)化問題是相當(dāng)普遍。一般來說，應(yīng)該優(yōu)化每一個目標(biāo)