本文選題：車輛路徑問題 + 城市配送　； 參考：《重慶交通大學》2015年碩士論文

【摘要】：隨著我國城鎮(zhèn)化進程的加快,城市規(guī)模越來越大,國家對物流業(yè)健康發(fā)展政策的大力支持,使得城市物流成為近年發(fā)展的熱點。城市物流系統(tǒng)是物流系統(tǒng)按區(qū)域劃分出的一種類別,城市物流是有貨物運輸、存儲、流通加工、配送等七種元素組成,其中配送是城市物流的核心因素之一,從系統(tǒng)上來說,城市物流配送網(wǎng)絡(luò)系統(tǒng)是城市物流系統(tǒng)的核心子系統(tǒng)之一。一個現(xiàn)代化的城市物流系統(tǒng)必須具有現(xiàn)代化的城市物流配送網(wǎng)絡(luò)系統(tǒng),完善優(yōu)化城市配送網(wǎng)絡(luò)就是以城市整體為本,按照客戶的要求,把貨物安全送達相應(yīng)的地點,在這個配送過程中,盡量使配送的車輛數(shù)、運營的里程數(shù)、對城市環(huán)境的污染等降到最少,這也是典型的車輛路徑問題。由于城市內(nèi)客戶點數(shù)量和布局、交通運輸、政策管理等特點,使得城市配送車輛路徑問題具有更多的限制和約束,所以結(jié)合城市配送實際,選擇客戶時間、道路行駛速度等因素,研究帶時間窗的時變條件下城市配送路徑優(yōu)化問題(TDVRPTW,Time-dependent Vehicle Routing Problem With Time Windows)。本文通過查閱大量文獻資料,首先總結(jié)了車輛路徑問題的概念及有關(guān)算法,詳細描述了城市物流配送系統(tǒng)的內(nèi)涵及功能,并對城市配送系統(tǒng)的特征及形成關(guān)鍵因素進行了分析研究;然后基于城市物流配送的特點及車輛路徑問題基本條件的界定,分析建立了帶時間窗的時變條件下城市配送路徑問題相關(guān)數(shù)學模型;最后對問題算法進行了研究,把聚類思想融入到路徑優(yōu)化算法中,設(shè)計了基于模糊聚類-人工蜂群兩階段啟發(fā)式算法:第一階段對客戶群進行模糊聚類分析,打破原有行政區(qū)劃,將客戶群劃分不同類別,降低原有問題的規(guī)模;第二階段對原有人工蜂群算法中的蜜源選擇概率公式進行改進,添加與迭代次數(shù)和蜂蜜優(yōu)良比率有關(guān)的擾動因子,解決算法迭代后期可能陷入局部最優(yōu)的缺點。使用Solomon設(shè)計的Benchmark Problems中的標準測試數(shù)據(jù)庫r101測試數(shù)據(jù),采用matlab編程,在算法第一階段進行聚類仿真,在算法第二階段對劃分的類別進行具體路線規(guī)劃實驗仿真,并與一般人工蜂群算法運算結(jié)果進行對比。最后以重慶市天友乳業(yè)股份有限公司自營專賣店配送為例,通過具體分析,對其具體配送路線進行了優(yōu)化。本文根據(jù)城市配送特點,提出符合城市配送實際的TDVRPTW問題數(shù)學模型,設(shè)計了模糊聚類-人工蜂群問題求解算法,通過實例分析驗證了模型的有效性及求解大規(guī)模問題時方法的可行性,有助于根據(jù)城市配送特征,制定更為合理城市配送方案,為優(yōu)化城市物流配送路線提供決策依據(jù)。
[Abstract]:With the acceleration of the urbanization process in China, the urban scale is more and more large, the country's strong support for the healthy development policy of the logistics industry has made the city logistics become a hot spot in recent years. The urban logistics system is a category divided by the regional logistics system, and the urban logistics has seven elements, such as cargo transportation, storage, circulation processing, distribution and so on. Distribution is one of the core factors of urban logistics. From the system, the urban logistics distribution network system is one of the core subsystems of the urban logistics system. A modern urban logistics system must have a modern urban logistics distribution network system, and the perfect optimization of urban distribution network is based on the whole city. In accordance with the requirements of the customer, the safety of the goods is sent to the corresponding location. In this process, the number of vehicles, the number of mileages operating and the pollution of the urban environment are reduced to the minimum. This is also a typical vehicle routing problem. The city is equipped with the characteristics of the number and layout of the customer points, transportation, policy management and so on in the city. Vehicle routing problem has more restrictions and constraints, so combining the actual distribution of urban distribution, choosing customer time, road speed and other factors, the problem of urban distribution path optimization (TDVRPTW, Time-dependent Vehicle Routing Problem With Time Windows) under the time window of time windows is studied. Firstly, the concept of vehicle routing problem and related algorithms are summarized, the connotation and function of urban logistics distribution system are described in detail, and the characteristics and key factors of urban distribution system are analyzed and studied. Then, based on the characteristics of urban logistics distribution and the definition of the basic conditions of the vehicle routing problem, the analysis has been made with time. The mathematical model of urban distribution path problem under the time varying condition of the window; finally, the problem algorithm is studied. The clustering idea is integrated into the path optimization algorithm, and the two stage heuristic algorithm based on fuzzy clustering and artificial bee colony is designed. The first stage of the clustering analysis of the customer group is carried out to break the original administrative division, and the customer group will be broken. Divide the different categories to reduce the size of the original problem; the second stage improves the probability formula of the nectar source selection in the original artificial bee colony algorithm, adds the disturbance factors related to the number of iterations and the good ratio of honey, and solves the problem that the algorithm may fall into the local optimal point in the later period of the iteration. The Benchmark Problems designed by Solomon is used. The standard test database R101 test data, using MATLAB programming, in the first stage of the algorithm clustering simulation, in the second stage of the algorithm of the classification of the specific route planning experiment simulation, and compared with the general artificial bee colony algorithm results. Finally, Chongqing Tianyou dairy industry Limited by Share Ltd distribution store distribution. For example, the specific distribution route is optimized through specific analysis. According to the characteristics of urban distribution, this paper puts forward a mathematical model of TDVRPTW problem which is in line with the actual distribution of urban distribution, and designs a fuzzy clustering and artificial bee colony problem solving algorithm. The validity of the model and the feasibility of solving the large-scale problem are verified by the case analysis. It helps to formulate a more reasonable urban distribution plan according to the characteristics of urban distribution, so as to provide decision-making basis for optimizing urban logistics distribution routes.
【學位授予單位】：重慶交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：U116.2

【參考文獻】

相關(guān)碩士學位論文 前1條

1 曹玉霞;基于模糊聚類分析和免疫算法的多車場帶時間窗問題的配送車輛路徑優(yōu)化研究[D];中國海洋大學;2012年

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本文編號：1898437