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Loading Optimization Method Based on Two Level Clustering

Author: ZhuLin
Tutor: LiBo
School: Tianjin University
Course: Management Science and Engineering
Keywords: Demand can be split under the Vehicle Routing Problem Artificial Immune Algorithm Hierarchical clustering Vehicle stowage
CLC: U492.22
Type: Master's thesis
Year: 2010
Downloads: 91
Quote: 1
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Abstract

With the development of enterprise globalization and outsourcing , large-scale logistics become a major problem facing many companies . Producer involving widely distributed , many product items , and fluctuations in customer demand , resulting in increased logistics LTL phenomenon . In order to reduce the cost of logistics , while fast response to customer demand , reduce distribution in LTL become a hot research vehicle stowage planning and scheduling . Based on this background, with two levels of priority vehicle stowage planning and scheduling methods . The introduction of an improved artificial immune algorithm (Artificial Immune Algorithm, AIA), through the development of this algorithm ideology and system clustering thinking , proposed a two -level vehicle stowage clustering method . Clustering algorithm is divided into two levels : first , on the level needs of the customer base clustering based on the geographic distribution of customers , the level of clustering only consider the positioning of the client , regardless of the demand for logistics ; then , the customer needs the orders are sorted according to the scheduling period , a vehicle stowage queue to be scheduled . Clustering scheme for the stowage of goods vehicles to the next level in this queue scheduling . In this case, the algorithm is based on the size of customer orders , customer demand items diversity and its distribution unit can not be divided and other characteristics , define a series of heuristic rules , consider renting the least number of vehicles and allow customers to split the case , the establishment of a mathematical model . Finally, the combination of heuristic strategies and a variety of sub- priority level clustering strategy , consider the customer is given a different product items, distribution integrity and the path to select the shortest to generate vehicle stowage clustering scheme . On the one hand , on the level of AIA customer clustering algorithm reduced the scope of the planning and scheduling of the next level vehicle loading clustering ; On the other hand , the next level with heuristic rules and priority level clustering model for a scheduling period a specific customer base vehicle stowage realization of the program . Practice large-scale logistics and distribution problems , the upper and lower levels of this article clustering algorithm designed to greatly reduce the complexity of the algorithm , the optimal solution available . Finally , the model simulation experiments , elaborate algorithm running steps , and the algorithm thinking is reflected to illustrate the effectiveness of the proposed method .

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