本文選題：動態(tài)客戶 + 同時取送貨��； 參考：《南京航空航天大學》2016年碩士論文

【摘要】：隨著我國經濟轉型戰(zhàn)略的不斷深化與發(fā)展,企業(yè)對于自身的管理提出了更高的要求,特別是在占綜合成本比例較高的物流管理方面。從企業(yè)角度出發(fā),居高不下的物流成本以及效率低下的配送方式,大大削弱了企業(yè)的競爭力。因此,配送方式及運輸成本作為影響物流成本和效率的主要因素,成為企業(yè)關注的重要問題以及研究的重點。一方面,從資源利用和節(jié)約能源的角度出發(fā),回收利用的逆向物流得到了更多的關注,越來越多的企業(yè)需要實行同時進行取貨和送貨的配送方式,以此來避免浪費有效提高資源利用率。另一方面,配送過程中出現的各種不確定信息會對既有的配送計劃產生極大影響,這也是企業(yè)需要解決的難題。移動通信技術、定位技術及智能設備的迅猛發(fā)展,為具有不確定信息的動態(tài)車輛路徑問題提供了解決基礎。因此,對符合現實情況的車輛路徑問題進行研究,能夠幫助企業(yè)降低成本,提高利潤,增強競爭力。本文選取不確定信息中的一類,即動態(tài)客戶問題,以更具效率的同時取送貨車輛路徑問題為依托展開研究,為企業(yè)解決車輛路徑問題提供借鑒,論文進行的主要工作如下:首先,簡明扼要的介紹了研究背景及意義,揭示了該研究的理論意義與現實價值,并對國內外針對該問題的研究做了總結與分析,闡明了論文的主要研究框架。其次,針對具有動態(tài)客戶的同時取送貨車輛路徑問題進行了理論介紹,明確該問題的定義、主要分類,常見的求解算法及其優(yōu)劣。文章選取蟻群算法作為解決問題的方法,并對該算法做了詳細的介紹,為后續(xù)的方法提出提供了基礎。第三,研究了不帶時間窗的具有動態(tài)客戶的同時取送貨車輛路徑問題,針對該問題的特點構建了數學模型。以蟻群優(yōu)化算法為基礎,結合實時插入方法,提出了符合問題特點的混合蟻群優(yōu)化算法ACS-RIM算法,并通過A公司的實例對算法的可行性進行了驗證,合理解決了帶有動態(tài)客戶并且沒有時間窗要求的VRPSDP問題。第四,研究了帶時間窗的具有動態(tài)客戶的同時取送貨車輛路徑問題,結合問題具有時間窗要求的特殊性,重新構建合適的數學模型。另外,改進了ACS-RIM算法,從節(jié)省資源降低成本的角度出發(fā),使算法的插入操作更能符合時間窗的要求,提高算法的求解速度和質量。通過對實際企業(yè)物流配送系統(tǒng)的優(yōu)化,有效解決資源浪費的問題,達到降低運輸成本,提高運輸效率的目的。
[Abstract]:With the deepening and development of China's economic transformation strategy, enterprises have put forward higher requirements for their own management, especially in the aspect of logistics management, which accounts for a high proportion of comprehensive cost. From the point of view of enterprises, the high logistics cost and inefficient distribution greatly weaken the competitiveness of enterprises. Therefore, distribution mode and transportation cost, as the main factors affecting logistics cost and efficiency, have become an important issue and research focus of enterprises. On the one hand, from the point of view of resource utilization and energy conservation, the reverse logistics of recycling has received more attention. More and more enterprises need to carry out the delivery of goods and delivery at the same time. In order to avoid waste and improve the efficiency of resource utilization. On the other hand, all kinds of uncertain information in the distribution process will have a great impact on the existing distribution plan, which is also a difficult problem that enterprises need to solve. With the rapid development of mobile communication technology, positioning technology and intelligent equipment, the dynamic vehicle routing problem with uncertain information is solved. Therefore, the research on the vehicle routing problem in accordance with the actual situation can help enterprises to reduce costs, improve profits and enhance competitiveness. In this paper, we select a kind of uncertain information, that is, dynamic customer problem, based on the more efficient delivery vehicle routing problem, to provide a reference for enterprises to solve the vehicle routing problem. The main work of this paper is as follows: firstly, the research background and significance are briefly introduced, the theoretical significance and practical value of the research are revealed, and the domestic and foreign research on this problem is summarized and analyzed. The main research framework of this paper is expounded. Secondly, the paper introduces the problem of taking delivery vehicle routing with dynamic customers, defines the problem, mainly classifies it, and discusses the common algorithm and its advantages and disadvantages. In this paper, ant colony algorithm is selected as the method to solve the problem, and the algorithm is introduced in detail, which provides the foundation for the following methods. Thirdly, the routing problem of dynamic customers with delivery vehicles without time window is studied, and a mathematical model is built according to the characteristics of the problem. Based on the ant colony optimization algorithm and the real-time insertion method, a hybrid ant colony optimization algorithm, ACS-RIM algorithm, is proposed, and the feasibility of the algorithm is verified by the example of A company. Reasonable solution to the VRPSDP problem with dynamic customers and no time window requirements. Fourthly, the vehicle routing problem with dynamic customers with time windows is studied. According to the particularity of time windows, an appropriate mathematical model is constructed. In addition, the ACS-RIM algorithm is improved to save resources and reduce the cost, so that the insertion operation of the algorithm can meet the requirements of the time window, and improve the speed and quality of the algorithm. By optimizing the logistics distribution system of actual enterprises, the problem of waste of resources is effectively solved, and the purpose of reducing transportation cost and improving transportation efficiency is achieved.
【學位授予單位】：南京航空航天大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：U116.2

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