夏德龙,吴耀华,王艳艳,等.基于智能机器人的“货到人”系统订单排序优化[J].深圳大学学报理工版,2019,36(6):696-701.[doi:10.3724/SP.J.1249.2019.06696]
XIA Delong,WU Yaohua,WANG Yanyan,et al.Order sequence optimization for parts-to-picker intelligent robot system[J].Journal of Shenzhen University Science and Engineering,2019,36(6):696-701.[doi:10.3724/SP.J.1249.2019.06696]
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基于智能机器人的“货到人”系统订单排序优化
夏德龙1,吴耀华1,王艳艳1,邹 霞2, 3

1)山东大学控制科学与工程学院,山东济南250061; 2)山东大学管理学院,山东济南250100; 3)山东财经大学管理科学与工程学院,山东济南250014

物流工程; “货到人”系统; 改进K-Means算法; 订单分拣; 智能机器人; 订单排序; 仿真

Order sequence optimization for parts-to-picker intelligent robot system
XIA Delong1, WU Yaohua1, WANG Yanyan1, and ZOU Xia2, 3

1)School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong Province, P.R.China2)School of Management, Shandong University, Jinan 250100, Shandong Province, P.R.China3)School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, Shandong Province, P.R.China

logistic engineering; parts-to-picker system; improved K-Means algorithm; order picking; intelligent robot; order sorting; simulation

DOI: 10.3724/SP.J.1249.2019.06696

备注

提出一种适用于“货到人”智能机器人系统的订单排序模型,通过优化订单拣选顺序,增加拣选台内相邻订单和拣选台之间订单的共用货架数量,减少货架的搬运次数,提高货架的出入库效率.把订单的排序看作旅行商问题(travelling salesman problem, TSP),并用改进K-Means聚类算法求解该订单排序模型.选取3组不同批次订单进行仿真验证,优化后系统货架搬运次数平均减少35.63%.

In this paper, we propose an order sorting model for the parts-to-picker intelligent robot system. By optimizing the sequence for order picking, the model increases the number of shared racks for orders within adjacent orders and picking stations, reduces the number of transportation times of the racks, thereby improving the efficiency of the warehouse system. Considering the order sequencing as the travelling salesman problem(TSP), we solve the order sorting model by the improved K-Means algorithm. Three sets of different batch orders are selected for simulation verification. After optimization, the transportation times of the system racks are reduced by 35.63% on average.

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