许小利,崔雪丽.基于遗传算法的分区拣选系统储位优化实证研究[J].包装工程,2015,36(19):139-144,148.
XU Xiao-li,CUI Xue-li.Storage Optimization Empirical Research of Zone Picking System Based on the Eenetic Algorithm[J].Packaging Engineering,2015,36(19):139-144,148. |
| 基于遗传算法的分区拣选系统储位优化实证研究 |
| Storage Optimization Empirical Research of Zone Picking System Based on the Eenetic Algorithm |
| 投稿时间：2015-01-16 修订日期：2015-10-10 |
| DOI： |
| 中文关键词: 分区拣选 遗传算法 储位优化 |
| 英文关键词: partition picking genetic algorithm storage space optimization |
| 基金项目:苏州科技学院研究生科研创新计划 （SKCX13S_038） |
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| 中文摘要: |
| 目的 研究零售连锁企业区域配送中心分区拣选系统下的储位优化方法。方法 以某药品连锁零售企业区域配送中心为研究对象， 将不同分区的拣选时间趋于均衡作为储位优化目标， 结合样本订单与历史订单的特点， 建立储位优化数学模型， 并采用遗传算法进行求解， 以获取约束条件内该模型的最优解。结果 在样本订单占80%权重的前提下， 将所求得的分区与储位的解所对应的拣选时间， 与研究对象的拣选现状进行对比， 发现采用均衡各区拣选时间模型的求解结果提高了37.34%的效率， 优化效果显著。结论 实证研究证明了该模型和算法的有效性， 该优化方法也广泛适用于其他分区拣选系统的储位分配作业。 |
| 英文摘要: |
| The aim of this work was to study the optimization of storage spaces in regional distribution centers of retail chains under the partition picking system. This paper took a pharmaceutical retail chain enterprise RDC as the object of study, set the zoning time balance as the goal of storage space optimization, established a mathematical model and used the genetic algorithm to achieve the solution in order to improve the efficiency of distribution center selection. Under the premise of sample orders accounting for 80% of the weight, comparing the chosen status of the study object with the picking time corresponding to the partitioning result and the storage location solved, we found that the solution based on the balancing picking time of different partition model increased by 37.34% in efficiency compared with the results, and the optimization effect was obvious. In conclusion, empirical studies have shown the effectiveness of the model and algorithm, and the optimization method is also widely applicable in the allocation of storage spaces in other partition picking systems. |
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