Robot Scheduling for Mobile-Rack Warehouses: Human-Robot Coordinated Order Picking Systems

成果类型:
Article
署名作者:
Wang, Zheng; Sheu, Jiuh-Biing; Teo, Chung-Piaw; Xue, Guiqin
署名单位:
Dalian Maritime University; National Taiwan University; National University of Singapore; National University of Singapore
刊物名称:
PRODUCTION AND OPERATIONS MANAGEMENT
ISSN/ISSBN:
1059-1478
DOI:
10.1111/poms.13406
发表日期:
2022
页码:
98-116
关键词:
robot scheduling Order picking human– machine coordination circadian rhythm Approximate Dynamic Programming
摘要:
Intelligent part-to-picker systems are spreading across a broad range of industries as preferred solutions for agile order fulfillment, wherein mobile racks are carried by robots and moved to stations where human pickers can pick items from them. Such systems raise the challenge of designing good work schedules for human pickers; they also give rise to a new class of operational scheduling problems in human-robot coordinated order picking systems. This work studies the problem of finding a suitable robot schedule that takes into account the schedule-induced fluctuation of the working states of human pickers. A proposed model enables mobile racks with various workloads to be assigned to pickers, and schedule the racks that are assigned to every picker to minimize the expected total picking time. The problem is formulated as a stochastic dynamic program model. An approximate dynamic programming (ADP)-based branch-and-price solution approach is used to solve this problem. The developed model is calibrated using data that were collected from a dominant e-commerce company in China. Pickers' working state transitions are modeled based on data obtained from this warehouse. Counter-factual studies demonstrate that the proposed approach can solve a moderately sized problem with 50 racks in under 2 minutes. More importantly, the approach yields high-quality solutions with picking times that are 10% shorter than the solutions that did not consider schedule-induced fluctuations of pickers' working states.