An improved crossover particle swarm optimization algorithm for automatic order sorting in distribution center

In this paper, the automatic order sorting problem with scattered storage is studied. First, the mathematical model of the problem is established. Then an improved crossover particle swarm optimization (CPSO) algorithm is proposed for order batching, batch sequencing and storage selection. The CPSO...

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Bibliographic Details
Published in2022 IEEE International Conference on Mechatronics and Automation (ICMA) pp. 1616 - 1621
Main Authors Xu, Yuze, Zhang, Linxuan, Li, Hui, Ge, Ming, He, Wanyi
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.08.2022
Subjects
Automatic order sorting
Automation
Crossover particle swarm optimization
Mathematical models
Mechatronics
Numerical models
Scattered storage
Search problems
Sequential analysis
Technological innovation
Variable neighborhood search
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Summary:In this paper, the automatic order sorting problem with scattered storage is studied. First, the mathematical model of the problem is established. Then an improved crossover particle swarm optimization (CPSO) algorithm is proposed for order batching, batch sequencing and storage selection. The CPSO mainly conducts the position update of particle swarm optimization algorithm by using crossover, which makes it more suitable for discrete problems. In order to enhance the local search capability of the algorithm, a variable neighborhood search (VNS) algorithm is proposed. And the neighborhood structure of the automatic order sorting problem for scattered storage is defined. The VNS will further search the neighborhood of the global optimal solution after each operation of the CPSO position update. Finally, the effectiveness of the proposed CPSO is verified by numerical experiments.
ISSN:2152-744X
DOI:10.1109/ICMA54519.2022.9856225