Computer Engineering and Applications ›› 2024, Vol. 60 ›› Issue (11): 356-366.DOI: 10.3778/j.issn.1002-8331.2303-0089

• Engineering and Applications • Previous Articles    

Research on RMFS Scheduling Problem Under Different Following Strategies

SI Congmin, WANG Zhuan   

  1. School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • Online:2024-06-01 Published:2024-05-31

不同跟随策略下RMFS调度问题研究

司聪敏,王转   

  1. 北京科技大学 机械工程学院,北京 100083

Abstract: With the rapid development of the e-commerce industry, RMFS is prevalent in the modern logistic center. As for this advanced system, robots can apply two following strategies:all-time following and non-following in a task. All-time following strategy means that robot follows the picking rack until the task is completed, and non-following strategy refers to that robot will leave the rack to perform other tasks when the rack is queued at the workstation, and the robot will be dispatched when the rack needs to be moved. For the robot scheduling problem under two kinds of following strategies, aiming at the shortest total time for the robot to complete the wave tasks, the robot scheduling models under two kinds of following strategies are designed. The simulation experimental platform under two kinds of following strategies are designed based on genetic algorithm, and the system performance of all-time following strategy and non-following strategy is compared through simulation experiments. The decision-making curve of the following strategy based on the shortest total time is obtained, and it is proved that selecting the appropriate following strategy, which is combined with the specific working conditions, can effectively improve the operation efficiency of the picking system. The application following strategy curve can help enterprises to choose robot following strategy.

Key words: robotic mobile fulfillment systems, following strategy, robot scheduling, simulation experimental platform

摘要: 随着电商行业的快速发展,移动机器人仓储系统(robotic mobile fulfillment systems,RMFS)在现代化物流中心被广泛应用。在RMFS中,机器人在一次分拣搬运任务中,可以采用完全跟随或不跟随两种策略,即机器人可以全程跟随拣选货架直至该任务完成;或者当货架在工作站排队时机器人离开货架去执行其他任务。针对两种跟随策略下的机器人调度问题,以机器人完成批次任务的总时间最短为目标,建立了两种跟随策略下的机器人调度模型,并基于遗传算法设计了两种跟随策略下的仿真实验平台,通过仿真实验对完全跟随与不跟随两种策略下的系统性能进行了比较,得出了基于完工时间最短的跟随策略决策决策曲线,证明结合具体工况选择合适的跟随策略能够有效提高拣货系统作业效率,利用跟随策略曲线可以帮助企业进行机器人跟随策略的选择。

关键词: 移动机器人仓储系统, 跟随策略, 机器人调度, 仿真平台