【摘要】：共同配送是配送發(fā)展的重要趨勢(shì)之一,其價(jià)值在于通過(guò)合作、資源共享降低物流成本、提高物流效率,同時(shí)削減在途運(yùn)行車(chē)輛,緩解城市交通壓力,節(jié)約社會(huì)資源、減輕環(huán)境污染。由于其存在的重要價(jià)值,共同配送在發(fā)達(dá)國(guó)家(如德國(guó)、日本)得到了廣泛的實(shí)踐應(yīng)用,在我國(guó),共同配送尚處于起步階段,隨著市場(chǎng)經(jīng)濟(jì)的發(fā)展,物流環(huán)境的不斷成熟以及物流成本、交通擁擠帶來(lái)的持續(xù)壓力,將促使共同配送在我國(guó)迅速發(fā)展。然而,共同配送企業(yè)在實(shí)際運(yùn)作中,存在著一些問(wèn)題亟待解決,例如,如何整合現(xiàn)有配送資源,如何降低配送車(chē)輛能耗,發(fā)揮更大的效益?本文首先分析了共同配送的運(yùn)作模式,通過(guò)對(duì)現(xiàn)有模式的分析得出共同配送的資源整合主要體現(xiàn)為三個(gè)方面：客戶資源、配送車(chē)輛資源和配送點(diǎn)資源,并在此基礎(chǔ)上建立了幾類(lèi)共同配送策略。其次,根據(jù)客戶資源共享的情況,考慮區(qū)域經(jīng)濟(jì)一體化過(guò)程中,供應(yīng)鏈的供應(yīng)企業(yè)或零售連鎖企業(yè)等,當(dāng)其公司發(fā)展到一定的規(guī)模后,存在有多個(gè)配送中心實(shí)行共同配送的情況,以滿足客戶差異性的商品需求,和日漸小批量、多批次的配送需求,需要考慮基于客戶差異性的情況來(lái)整合客戶資源,提高配送效率和服務(wù)水平。文中構(gòu)建了客戶分組條件下的多配送點(diǎn)車(chē)輛路徑模型,以配送距離最短為優(yōu)化目標(biāo),在遺傳算法的基礎(chǔ)上進(jìn)行算法設(shè)計(jì),通過(guò)設(shè)計(jì)插入變異改變配送中心客戶群數(shù)量,提高路徑搜索的廣度,并將改進(jìn)算法與傳統(tǒng)算法在運(yùn)行結(jié)果上進(jìn)行了對(duì)比分析,并進(jìn)一步分析了不同種群下的尋優(yōu)過(guò)程。再次,根據(jù)配送車(chē)輛共享的情況,考慮實(shí)際配送運(yùn)作中,客戶需求的變化性,配送車(chē)輛在完成每階段最后一個(gè)客戶點(diǎn)的配送服務(wù)后,無(wú)需回到出發(fā)車(chē)場(chǎng),可選擇就近車(chē)場(chǎng)�？炕蛞罁�(jù)資源共享降低成本的原則,將車(chē)輛�？吭陂_(kāi)放的協(xié)同企業(yè)車(chē)場(chǎng)。每次配送階段均為獨(dú)立的,隨著客戶需求的變化,配送車(chē)場(chǎng)的配送車(chē)輛隨著不斷變化的配送需求而調(diào)整車(chē)場(chǎng)車(chē)輛數(shù)。文中構(gòu)建了車(chē)場(chǎng)開(kāi)放條件下的多配送點(diǎn)車(chē)輛路徑模型,以配送距離最短為優(yōu)化目標(biāo),在粒子群算法的基礎(chǔ)上進(jìn)行了算法設(shè)計(jì),通過(guò)對(duì)粒子更新進(jìn)行設(shè)計(jì),提高算法的搜算廣度,避免陷入局部最優(yōu),并將改進(jìn)算法與傳統(tǒng)粒子群算法進(jìn)行對(duì)比分析。最后,討論配送車(chē)輛在實(shí)際的配送行駛中,由于配送距離的變化,配送時(shí)間的約束,以及實(shí)際配送速度與城市車(chē)輛限速等不同情況下的車(chē)輛行駛能耗分析,并進(jìn)行了仿真測(cè)試,為城市配送車(chē)輛在距離、時(shí)間、速度等不同條件下,選擇節(jié)能低碳的配送車(chē)輛行駛模式提供參考依據(jù)。
[Abstract]:Joint distribution is one of the important trends in the development of distribution. Its value lies in reducing logistics cost and improving logistics efficiency through cooperation, resource sharing, and at the same time reducing the running vehicles on the way, relieving the pressure of urban traffic and saving social resources. Reduce environmental pollution. Because of its important value, joint distribution has been widely used in developed countries (such as Germany, Japan). In China, joint distribution is still in its infancy, with the development of market economy. The maturation of logistics environment and the continuous pressure of logistics cost and traffic congestion will promote the rapid development of joint distribution in China. However, in the actual operation of joint distribution enterprises, there are some problems to be solved. For example, how to integrate the existing distribution resources, how to reduce the energy consumption of distribution vehicles, and how to play a greater benefit? This paper first analyzes the operation mode of joint distribution, and through the analysis of the existing model, it is concluded that the integration of common distribution resources is mainly reflected in three aspects: customer resources, distribution vehicle resources and distribution point resources. On this basis, several common distribution strategies are established. Secondly, according to the situation of customer resource sharing, considering the process of regional economic integration, supply enterprises or retail chain enterprises in the supply chain, when their companies develop to a certain scale, There are many distribution centers to implement joint distribution to meet the needs of different customers, and smaller and more batches of distribution needs, need to consider the situation based on customer differences to integrate customer resources, Improve delivery efficiency and service level. In this paper, a multi-point vehicle routing model under the condition of customer grouping is constructed. With the shortest distribution distance as the optimization goal, the algorithm is designed on the basis of genetic algorithm, and the number of customers in distribution center is changed by inserting variation. The improved algorithm is compared with the traditional algorithm in the running results, and the optimization process under different populations is further analyzed. Thirdly, according to the situation of distribution vehicle sharing, considering the variability of customer demand in actual distribution operation, the distribution vehicle does not need to return to the departure yard after completing the distribution service of the last customer point in each stage. According to the principle of reducing the cost of resource sharing, the vehicle can be parked in the open cooperative enterprise yard. Each distribution stage is independent, with the change of customer demand, the distribution vehicle of the distribution yard adjusts the number of vehicles with the changing distribution demand. In this paper, the vehicle routing model of multi-distribution points under the condition of open vehicle yard is constructed. With the shortest distribution distance as the optimization goal, the algorithm is designed on the basis of particle swarm optimization algorithm, and the search breadth of the algorithm is improved by designing the particle update. To avoid falling into local optimum, the improved algorithm is compared with the traditional particle swarm optimization algorithm. Finally, the paper discusses the energy consumption analysis of distribution vehicles under different conditions, such as the variation of distribution distance, the constraint of distribution time, and the actual distribution speed and the speed limit of urban vehicles, and carries out simulation tests. This paper provides a reference for the choice of energy saving and low carbon distribution vehicle driving mode under different conditions such as distance, time, speed and so on.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F252

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本文編號(hào)：2202403