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Optimization Method Study Of Multi-center Location For Urban Logistics Distribution

Posted on:2020-10-15Degree:MasterType:Thesis
Country:ChinaCandidate:S Q HuangFull Text:PDF
GTID:2439330572986599Subject:Engineering
Abstract/Summary:PDF Full Text Request
With the development of The Times,urban distribution has been paid more and more attention.As the basis of urban economic and social development,urban distribution is of great importance to the optimal allocation and comprehensive development of urban resources.At present,compared with some developed countries,there are still deficiencies in urban distribution.The logistics distribution system lacking of the level,cannot form the integration development of city distribution.The multi-functional distribution center and other infrastructure construction is not perfect,resulting logistics distribution in low efficiency and serious waste of resources.In order to meet the test of the new era and improve the efficiency of urban logistics distribution,the entire urban distribution system is optimized from the construction of logistics infrastructure.As a transportation hub in the whole urban distribution system,distribution center plays an important role and has great value.In this paper,based on the research of domestic and foreign relevant location research method,in view of city logistics distribution center location factors in the process of selection and integration methods of for urban logistics distribution center as the research object,put forward more distribution centers location comprehensive evaluation method and the total cost and logistics system,the mathematical model of reliability as the objective function method of distribution center location method is optimized.Firstly,an index evaluation system is established to influence the decision of multicenter location of urban logistics and distribution.The method of combining the value of language variables and the trapezoidal intuitionistic fuzzy number is used to obtain the comprehensive evaluation value of each distribution center under the criterion index.Secondly,according to the membership function,the integrated comprehensive evaluation value is divided into three sub-attribute values,and the sub-attribute value is taken as the input of the clustering process.Then,k-means method is used for clustering analysis of each candidate distribution center.Finally,TOPSIS method was used to rank the candidate logistics distribution centers in each cluster unit,and then the optimal location scheme of urban logistics distribution centers was obtained.The result of the example analysis proves the rationality and reliability of the fuzzy comprehensive site selection method.Because the fuzzy comprehensive location method is affected by subjective factors to some extent,the multi-center location problem of urban logistics distribution based on cost and reliability is studied by quantitative analysis method.Firstly,the paper analyzes the relevant factors affecting the location of multi-center of urban logistics and distribution,and takes cost and customer satisfaction as important indicators affecting the location of multi-center of urban logistics and distribution.The concept of logistics distribution reliability is introduced to express customer satisfaction.Secondly,a twoobjective mathematical model with the objective function of cost minimization and logistics distribution reliability maximization is established.Then,the dual objective mathematical model is transformed into a single objective mathematical model by the main objective method,and the greedy algorithm is used to solve the problem.Finally,the practicability and reliability of the proposed method are proved by an example.It is more suitable for the practical situation of urban logistics distribution to use the quantitative method to select the location of multiple centers of urban logistics distribution,and this method can also be applied to the relevant research in other fields.
Keywords/Search Tags:Multiple distribution center location, Fuzzy comprehensive evaluation method, K-means clustering method, Quantitative analysis, Greedy take away heuristic algorithm
PDF Full Text Request
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