Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (12): 31-36.

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Priority-based genetic algorithm for routing automated guided vehicles for traversing blocks in warehouse aisles

HOU Xiaoqin1, HU Zhihua1, GAO Chaofeng1, LUO Xunjie2   

  1. 1.Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
    2.Shanghai International Ports Group Ltd., Shanghai 200137, China
  • Online:2016-06-15 Published:2016-06-14

自动化仓库巷道网络AGV货区遍历优化——设计基于优先权遗传算法实现

侯晓琴1,胡志华1,高超峰1,罗勋杰2   

  1. 1.上海海事大学 物流研究中心,上海 201306
    2.上海国际港务集团,上海 200137

Abstract: A block-layout based routing problem of network configurations in an automation warehouse, plant or terminal is considered as an automated local logistics storage system. It aims at finding out the shortest path that traverses all blocks. A mixed-integer linear program is established to formulate the problem under the minimization of the path. Besides, a priority-based genetic algorithm is developed and realized using the tool of Matlab to solve the model. In the end, the genetic operators are analyzed by experimental comparisons and the algorithm is validated by experiments.

Key words: automated guided vehicle, block-layout, traversing, shortest path, genetic algorithm, priority, automated warehouse

摘要: 针对自动化仓库、自动化车间及自动化码头等自动化局部物流存储系统仓库巷道网络中AGV(自动化导引车)对仓库货区遍历作业的路径优化问题,以搜索遍历所有货区的最短路径为目标,建立混合整数线性规划模型,并设计基于优先权的遗传算法求解。通过Matlab仿真实验分析比较算子性能,验证算法的有效性。

关键词: 自动化导引车, 货区布局, 遍历, 最短路径, 遗传算法, 优先权, 自动化仓库