考虑拣选疲劳的机器人履约系统多目标调度模型  

Multi-objective scheduling model of robot mobile fulfillment system considering picking fatigue

作　　者：李腾[1] 丁佩佩 张茹兰 LI Teng;DING Peipei;ZHANG Rulan(Management School,Harbin University of Commerce,Harbin 150028,China)

机构地区：[1]哈尔滨商业大学管理学院,黑龙江哈尔滨150028

出　　处：《管理工程学报》2025年第3期136-152,共17页Journal of Industrial Engineering and Engineering Management

基　　金：教育部哲学社科后期重大项目(22JHQ009);黑龙江省博士后科研启动金项目(LBH-Q21102);黑龙江省自然科学基金项目(LH2023G009)。

摘　　要：在移动机器人与拣选人员协同完成拣选工作的机器人履约系统中,在机器人充足且不间断工作的情况下,本文重点关注由拣选人员决定的拣选工作站处工作效率。本文考虑疲劳因素对拣选人员工作效率的影响,首先建立了以拣选人员任务完成时间最短为目标的模型,然而仅考虑优化上述目标会造成多机器人在拣选工作区排队等待,系统出现冲突阻塞;然后建立以所有机器人排队等待时间最短为目标的模型,机器人分配结果为决策变量。考虑机器人排队等待将对拣选人员产生的心理压力,本文采用约束法对拣选人员任务完成时间进行约束处理,利用遗传算法对模型进行求解。算例仿真实验验证了考虑拣选疲劳能够提升拣选工作站处工作效率,订单拣选难度越大,模型优化效果越显著。本文通过仿真分析得出如下结论:同批任务中,优先分配拣选难度小的任务会使拣选效率更高;分配储位时各货架层的拣选难度差异越小,拣选效率越高。最后,本文分析影响拣选疲劳的各项参数,所提出的模型适应不同拣选人员及不同工作状态,符合基于组织积极性学说的组织管理理念,能够使拣选人员保持高水平的体能和心理沉浸感。The scarcity of labor resources and the sustained increase in human capital costs have escalated human risks and labor costs in labor-intensive enterprises.This has been mitigated by the advent of mobile robot fulfillment systems(RMFSs),which have reduced the high labor intensity in warehouse picking systems and the workloads of picking personnel.The picking task in RMFSs is executed collaboratively between mobile robots and picking personnel.The behavior and working status of mobile robots are precisely regulated by the system,resulting in consistent and reliable performance regarding their work status and efficiency.Nevertheless,the efficiency of picking personnel remains contingent on various factors,resulting in uncertainties in the overall system efficiency.Hence,it is crucial to prioritize ensuring and enhancing the efficiency of the picking workstation during the overall planning of an RMFS.In an RMFS,the most subjective and uncontrollable agent is the picker who executes the picking operation at the picking workstation.When there is an adequate number of robots working continuously,the efficiency of pickers cannot be constantly maintained.If the fatigue of pickers is not considered when developing a robot scheduling scheme,the picking workstation will become a system bottleneck.This paper presents our investigation of the effect of fatigue factors on picking efficiency and proposes a human-robot collaborative robot scheduling scheme that considers picking fatigue.The continuous work required of picking personnel inevitably leads to fatigue.In a multi-robot scheduling scheme that fails to account for picking personnel fatigue,there will be a significant and random deviation between the actual and expected picking completion time.As the number of tasks completed increases,this deviation will increase.In this study,we studied the effect of picker fatigue factors on robot scheduling decisions by comprehensively analyzing the causes and effects of picking fatigue on picking efficiency.Based on our insights,we

关 键 词：RMFS 拣选疲劳 机器人调度 多目标优化 遗传算法 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置] F724.6[自动化与计算机技术—控制科学与工程]