基于分拣机器人零售电商订单动态聚类及仿真

王晨, 尹静, 王红春

包装工程(技术栏目) ›› 2020 ›› Issue (3) : 170-175.

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PDF(394 KB)
包装工程(技术栏目) ›› 2020 ›› Issue (3) : 170-175. DOI: 10.19554/j.cnki.1001-3563.2020.03.026

基于分拣机器人零售电商订单动态聚类及仿真

  • 王晨1, 尹静1, 王红春2
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Dynamic Clustering and Simulation of Retail E-commerce Order Based on Sorting Robot

  • WANG Chen1, YIN Jing1, WANG Hong-chun2
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摘要

目的 提高电商物流配送中心订单的分拣效率和动态响应能力。方法 通过分析零售电商订单的多品种、小批量和高时效等特征,考虑分拣机器人动作与载重约束,提出了滚动时窗调度策略和高维稀疏动态聚类算法,并以某大型电商企业配送中心建立仿真实验模型,进行数据对比分析。结果 以某大型电商某日高峰时段500个订单进行仿真实验,与固定组批分拣策略进行对比,优化后的分拣策略在机器人平均搬运距离上减少了66.9%,分拣时间降低了23.9%。结论 高维稀疏动态聚类策略有效提高了分拣效率,降低了分拣成本,算法方式更加开放灵活,对于电商企业物流业务降本增效具有重要意义。

Abstract

The work aims to improve the sorting efficiency and dynamic response capability of orders for e-commerce logistics distribution centers. Based on analyzing such factors as the characteristics of retail e-commerce orders with multiple varieties, small batches and high aging, movement and load constraints of sorting robots were taken into consideration; a rolling window scheduling strategy and a high-dimensional sparse dynamic clustering algorithm were proposed, and a simulation experiment model of a large-scale e-commerce distribution center was established for data comparison analysis. The simulation experiment was carried out on 500 orders of an e-commerce enterprise in rush hours. Compared with the fixed batch sorting strategy, the optimized sorting strategy reduced the average moving distance of the robot by 66.9% and the sorting time by 23.9%. The conclusion is that the high-dimensional sparse dynamic clustering strategy effectively improves the sorting efficiency, reduces the sorting cost, and the algorithm is more open and flexible. It is of great significance for the e-commerce enterprise to reduce costs and increase efficiency of logistics business.

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王晨, 尹静, 王红春. 基于分拣机器人零售电商订单动态聚类及仿真[J]. 包装工程(技术栏目). 2020(3): 170-175 https://doi.org/10.19554/j.cnki.1001-3563.2020.03.026
WANG Chen, YIN Jing, WANG Hong-chun. Dynamic Clustering and Simulation of Retail E-commerce Order Based on Sorting Robot[J]. Packaging Engineering. 2020(3): 170-175 https://doi.org/10.19554/j.cnki.1001-3563.2020.03.026

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国家自然科学基金(61772062)

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