DOI number:10.3390/su13105644
Affiliation of Author(s):中南大学交通运输工程学院
Teaching and Research Group:交通运输工程系
Journal:sustainability
Place of Publication:Switzerland
Key Words:automatic warehousing system; green technology; robotic mobile fulfillment system (RMFS); storage location assignment; path planning; A-star algorithm
Abstract:The robotic mobile fulfillment system (RMFS) is a new automatic warehousing system, a type of green technology, and an emerging trend in the logistics industry. In this study, we take an RMFS as the research object and combine the connected issues of storage location assignment and path planning into one optimization problem from the perspective of collaborative optimization. A sustainable mathematical model for the collaborative optimization of storage location assignment and path planning (COSLAPP) is established, which considers the relationship between the location assignment of goods and rack storage and path planning in an RMFS. On this basis, we propose a location assignment strategy for goods clustering and rack turnover, which utilizes reservation tables, sets AGV operation rules to resolve AGV running conflicts, and improves the A-star(A*) algorithm based on the node load to find the shortest path by which the AGV handling the racks can complete the order picking. Ultimately, simulation studies were performed to ascertain the effectiveness of COSLAPP in the RMFS; the results show that the new approach can significantly improve order picking efficiency, reduce energy consumption, and lessen the operating costs of the warehouse of a distribution center.
Co-author:Yue Liang, Shan Ouyang
First Author:Jianming Cai
Indexed by:Journal paper
Correspondence Author:Xiaokang Li
Document Code:5644
Discipline:Engineering
First-Level Discipline:Transportation Engineering
Document Type:J
Volume:13
Issue:10
Page Number:https://doi.org/10.3390/su13105644
Translation or Not:no
Included Journals:SCI
Links to published journals:https://doi.org/10.3390/su13105644