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A distributed spare parts warehouse allocation strategy for automobile industry chain based on parallel genetic algorithm

机译:基于并行遗传算法的汽车产业链分布式备件仓库分配策略

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Aimed at inventory allocation needs with timeliness and accuracy of distributed spare parts warehouses, a collaborative allocation model for spare parts is proposed. Based on an analysis of the characteristics and defects of the genetic algorithm, a distributed inventory allocation strategy based on the parallel genetic algorithm is proposed, and a coarse parallel genetic algorithm within the framework of MapReduce is realized. The proposed strategy and algorithm together reduce the heavy computation burden during the process of problem-solving which is based on the genetic algorithm. Effectiveness of the proposed strategy is verified based on the spare parts inventory data of providers on the automobile industry chain.
机译:旨在具有分布式备件仓库的及时性和准确性的库存配置需求,提出了一种备件的协作分配模型。基于对遗传算法的特征和缺陷的分析,提出了一种基于并行遗传算法的分布库存分配策略,实现了MAPRADUCE框架内的粗平行遗传算法。所提出的策略和算法在一起减少了基于遗传算法的解决问题过程中的重计算负担。拟议策略的有效性是根据汽车产业链上提供商的备件库存数据核实。

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