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A Dual-Colony Ant Algorithm for the Receiving and Shipping Door Assignments in Cross-Docks

Authors
Zhang, Yu-HuiGong, Yue-JiaoChen, Wei-NengGu, Tian-LongYuan, Hua-QiangZhang, Jun
Issue Date
Jul-2019
Publisher
Institute of Electrical and Electronics Engineers
Keywords
Ant colony system; assignment problem; combinatorial optimization; cross-docking; heuristic algorithm
Citation
IEEE Transactions on Intelligent Transportation Systems, v.20, no.7, pp 2523 - 2539
Pages
17
Indexed
SCI
SCIE
SCOPUS
Journal Title
IEEE Transactions on Intelligent Transportation Systems
Volume
20
Number
7
Start Page
2523
End Page
2539
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115459
DOI
10.1109/TITS.2018.2867577
ISSN
1524-9050
1558-0016
Abstract
Cross-docks serve as distribution centers where shipments from different vendors are first consolidated according to their destinations, and then delivered to the retailers directly, with little or no storage in between. A critical problem encountered in the operation of cross-docks is the assignment of receiving and shipping doors, which greatly influences the labor or machinery cost of transferring the shipments between inbound and outbound transports. We show that the cross-dock door assignment problem (CDAP) is strictly non-deterministic polynomial-time complete. Although some deterministic algorithms have been reported to handle small-scale problems, the solutions to the middle- and large-scale CDAPs progressed at a slow pace. In this paper, we develop a nature-inspired dual-colony ant algorithm for CDAP, in which the two colonies of ants cooperatively search the optimal assignments of receiving and shipping doors to minimize the transferring costs of shipments. A collaborative local search strategy is designed and incorporated into the algorithm to enhance the search efficiency. Experiments have been conducted on a number of problem instances with different cross-dock sizes and freight flow patterns. The results show that the proposed algorithm is very competitive and can provide better solutions than the state-of-the-art heuristic algorithms. © 2000-2011 IEEE.
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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