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A class-based storage warehouse design using a particle swarm optimisation algorithm

机译:使用粒子群优化算法的基于类的存储仓库设计

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Classical warehouse design is commonly done in two steps by first determining the aisle layout and dimension followed by the assignment of items to storage. The design process is performed iteratively until a design with appropriate performance criterion is found. This paper proposes an approach for warehouse design in one step by determining the aisle layout and dimension while simultaneously assigning shelf spaces for storing the items based on item classes. A mathematical model is formulated to determine the number of aisles, the length of aisle and the length of each pick aisle to allocate to each product class that will minimise the average travel distance for & warehouse that operates under a class-based storage policy. A particle swarm optimisation algorithm was developed to determine the optimal warehouse design. The proposed method not only accomplishes the task in one step but also can identify multiple alternative designs. A case study is used to illustrate the proposed algorithm.
机译:经典的仓库设计通常分两个步骤完成,首先确定通道的布局和尺寸,然后分配要存储的物品。迭代执行设计过程,直到找到具有适当性能标准的设计为止。本文通过确定过道的布局和尺寸,同时根据物料类别分配用于存储物料的货架空间,一步一步地提出了一种仓库设计方法。制定了数学模型,以确定过道的数量,过道的长度和每个拣货过道的长度,以分配给每个产品类别,这将最大程度地减少基于类存储策略的仓库的平均行进距离。开发了粒子群优化算法来确定最佳仓库设计。所提出的方法不仅可以一步完成任务,而且可以识别多种替代设计。通过案例研究来说明该算法。

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