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The Optimization of Automated Stereoscopic Warehouse's Cargo Space Allocation Based on Hybrid Particle Swarm Algorithm

机译:基于混合粒子群算法的立体仓库自动化货位分配优化

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It proposes the decision module which based on the combination of polychromatic set and hybrid particle swarm algorithm. It uses polychromatic set theory to carry on partition to the shelves; the partition of each row of shelves is the same and the number of partitions is the same as the number of type of goods, then it uses particle swarm algorithm to determine the warehousing quantity of each kind of goods in each row of shelves, and finally in each row of shelves, according to the types and quantities of inbound goods, it uses hybrid particle swarm algorithm to carry on specific allocation to warehousing storage space in the corresponding regions, solves the problem of storage location assignment's optimization, and proves this module's feasibility and effectiveness through examples.
机译:提出了基于多色集合与混合粒子群算法相结合的决策模块。它采用多色集合理论对货架进行划分;每排货架的分区相同,且分区数量与商品种类的数量相同,然后使用粒子群算法确定各排货架上每种商品的入库数量,最后在每一排货架上,根据入库货物的种类和数量,采用混合粒子群算法对相应区域的仓储空间进行具体分配,解决了仓储位置分配的优化问题,证明了该模块的可行性。通过示例来提高效率。

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