An effective multi-AGVs dispatching method applied to matrix manufacturing workshop

[Display omitted] •A multi-AGVs dispatching method to minimize the transportation cost is addressed.•An improved iterated greedy (IIG) algorithm is proposed.•An AGV route merging strategy and a workshop partition strategy are designed.•Two rules are designed to reduce the number of infeasible soluti...

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Veröffentlicht in:Computers & industrial engineering Jg. 163; S. 107791
Hauptverfasser: Zhang, Xu-jin, Sang, Hong-yan, Li, Jun-qing, Han, Yu-yan, Duan, Peng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.01.2022
Schlagworte:
Dispatching
Iterated greedy algorithm
Matrix manufacturing workshops
Multi-AGVs
Multi-AGVs
Iterated greedy algorithm
Matrix manufacturing workshops
Dispatching
ISSN:0360-8352
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Zusammenfassung:[Display omitted] •A multi-AGVs dispatching method to minimize the transportation cost is addressed.•An improved iterated greedy (IIG) algorithm is proposed.•An AGV route merging strategy and a workshop partition strategy are designed.•Two rules are designed to reduce the number of infeasible solutions.•A repair strategy is proposed. This paper studies the problem of multiple automatic guided vehicles (multi-AGVs) dispatching in a matrix manufacturing workshop. The goal is to minimize the transportation cost that includes the cost of travelling distance, the cost of penalty time and the cost of AGVs. For the purpose, a mixed integer linear programming model is set up and an improved iterated greedy (IIG) algorithm is proposed. In the algorithm, an AGV route merging strategy and a workshop partition strategy are designed to reduce the cost of AGVs and travelling distance. Two rules are designed to quickly identify infeasible solutions to save the operation time. A nearest neighbor heuristic is used to generate an initial solution with high quality. In the local search stage, four effective operators are used to improve the quality of the solution. A repair strategy is proposed to avoid the algorithm falling into local optima. Finally, we use 110 real instances to test the IIG and the other six algorithms in the literature. The comparative experiments show that the proposed algorithm and strategies have much better performance for solving this problem.
ISSN:0360-8352
DOI:10.1016/j.cie.2021.107791