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1、分類號(hào):U49;F510710—20050807諼害夫淫碩士學(xué)位論文基于捕食搜索策略粒子群算法的車輛路徑問(wèn)題研究導(dǎo)師姓名職稱申請(qǐng)學(xué)位級(jí)別論文提交13期學(xué)位授予單位喬燁陳煥江教授答辯委員會(huì)主席郭曉汾教授學(xué)位論文評(píng)閱人胡大偉教授朝承斌教授級(jí)高工捅芰隨著社會(huì)分工深化和經(jīng)濟(jì)快速發(fā)展,物流的功能和作用也在不斷加強(qiáng)。物流系統(tǒng)研究的重點(diǎn)是物流配送的優(yōu)化。在現(xiàn)實(shí)生活中,為了使物流配送企業(yè)優(yōu)化配送路徑、降低配送成本和提高經(jīng)營(yíng)管理水平,增加企業(yè)的競(jìng)爭(zhēng)能力,必須對(duì)配送問(wèn)題中車輛路徑問(wèn)題進(jìn)行深入地研究。車輛路徑問(wèn)題不僅是配送問(wèn)題中的核心
2、,也是研究的焦點(diǎn)之一。在實(shí)際中合理安排車輛路徑能有效提高運(yùn)輸效率,降低服務(wù)成本。自車輛路徑問(wèn)題提出以后,國(guó)內(nèi)外的專家學(xué)者就對(duì)其開(kāi)展了廣泛的研究。目前己經(jīng)產(chǎn)生出多種成熟的算法,為后人繼續(xù)研究提供了基礎(chǔ)。本文首先分析了車輛路徑問(wèn)題的研究現(xiàn)狀,給出了車輛路徑問(wèn)題的一般描述及分類,并對(duì)常用求解車輛路徑問(wèn)題的算法進(jìn)行了總結(jié)。其次,介紹了粒子群算法的基本概念、數(shù)學(xué)模型和算法流程以及捕食搜索策略的基本思想及算法流程。在此基礎(chǔ)上,本文設(shè)計(jì)了一種對(duì)車輛路徑問(wèn)題進(jìn)行求解的算法一基于捕食搜索策略的粒子群算法。該算法通過(guò)對(duì)捕食搜索策略限
3、制的調(diào)節(jié),來(lái)實(shí)現(xiàn)粒子群算法搜索空間的增大或減小,從而達(dá)到探索能力和開(kāi)發(fā)能力的平衡,使粒子群算法求得更好的最優(yōu)解。用C++語(yǔ)言編程實(shí)現(xiàn)并將其應(yīng)用于實(shí)例,優(yōu)化了實(shí)例中的車輛路徑,證明了該算法的有效性和可行性。最終得出該算法是求解車輛路徑問(wèn)題的一個(gè)可行方法的結(jié)論。關(guān)鍵詞:配送,車輛路徑問(wèn)題,粒子群算法,捕食搜索策略AbstractWiththedeepeningofthesocialdivisionoflaboranddevelopingofeconomic,thefunctionandroleofthelogisti
4、csareexpanding.Asanimportantpartofthelogisticssystem,thelogisticssystemresearchfocusonlogisticsdistributionoptimization.Practically,inordertomakelogisticsdistributionenterprisesoptimizethedistributionpath,reducedistributionCOSTSandimprovelogisticsmanagementan
5、dincreasethecompetitivenessoftheenterprises,logisticsdistributionofVehicleRoutingProblem(VRP)hasbeenincreasinglyimportant.TheVRPisnotonlythecoreoflogisticsdistribution,butalsooneofthefocusofresearch。Inreality,reasonablearrangementsforvehicleroutingcanimprovet
6、ransportefficiencyandreduceservicecostseffectively.SincetheVRPwasputforward,theexpertsandscholarshavecarriedoutextensiveresearch.Ithasbeenmanymaturealgorithmthatprovidedbasisforcontinuingthequestion.Firstly,thispaperanalyzedthestatusquooftheVRP,describtedandc
7、lassifiedthegeneralVRP,andsummarizedtheexistingalgorithmforsolvingVRP.Secondly,itintroducedtheParticleSwarmOptimization(PSO)onbasicconcepts,mathematicalmodelsandalgorithmsprocess.Lastly,itdescribedthePredatorSearchstrategy.Onthisbasis,inordertosolvetheVRP,the
8、PSOalgorithmbasedonthePredatorSearchstrategywasdesignedinthispaper.ItregulatedtherestrictionsofthePredatorSearchstrategy,forachievingincreaseordecreaseinthePSOsearchspace.Moreover,itbalan