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作 者:王晨 尹静 王红春[2] WANG Chen;YIN Jing;WANG Hong-chun(School of Mechanical and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 102616,China;School of Economics and Management,Beijing University of Civil Engineering and Architecture,Beijing 102616,China)
机构地区:[1]北京建筑大学机电与车辆工程学院,北京102616 [2]北京建筑大学经济管理学院,北京102616
出 处:《包装工程》2020年第3期170-175,共6页Packaging Engineering
基 金:国家自然科学基金(61772062)
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。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.
关 键 词:电商物流订单 分拣机器人 动态聚类 分拣策略 仿真
分 类 号:TB486[一般工业技术—包装工程] TH691.5[机械工程—机械制造及自动化]
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