Application of Genetic Algorithm in Functional Area Layout of Railway Logistics Park

被引:12
|
作者
Zhang, Qi [1 ]
Jiang, Chunsheng [2 ]
Zhang, Jing [1 ]
Wei, Yuguang [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[2] China Railway SIYUAN Survey & Design Grp Co Ltd, Wuhan 430063, Peoples R China
关键词
Logistics park; functional area layout; comprehensive relationship; genetic algorithm; Matlab;
D O I
10.1016/j.sbspro.2014.07.204
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
As a new type of logistics network nodes, the logistics park is a significant part of the logistics system. Planning and constructing logistics parks scientifically is conducive to not only the construction of modern logistics environment but also the realization of the parks' function and the whole benefit of the logistics system. Realization of the optimal layout of functional areas with appropriate methods is the basis of logistics park planning and construction. Accordingly, the internal layout of each functional area can be further designed. In this paper, the genetic algorithm is adopted to solve the functional areas layout optimization problem of the railway logistics parks. After getting the comprehensive relationship chart of the different functional areas, the paper solved the layout problem with mathematical methods instead of the traditional manual adjustment method. Combined with relevant constraint conditions, the paper constructed the model taking the maximal arithmetic product of comprehensive relationship and adjacency degree as the objective function. Then the article coded with Matlab based on genetic algorithm. The model was testified to its feasibility and rationality by a practical illustrative example. In this paper, the functional area layout problem of the logistics park was regarded as a mathematical optimization problem, so that the uncertainties of layout affected by subjective factors was reduced to a certain extent combining qualitative analysis with quantitative analysis. The application of genetic algorithm in the layout optimization model greatly improved the quantifiable accuracy which provided a new thought for the functional areas layout of railway logistics parks. (C) 2014 Published by Elsevier Ltd.
引用
收藏
页码:269 / 278
页数:10
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