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Article

Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line

1
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
School of Mechanical Engineering, Yancheng Institute of Technology, Yancheng 224051, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2022, 12(21), 10956; https://doi.org/10.3390/app122110956
Submission received: 15 September 2022 / Revised: 14 October 2022 / Accepted: 26 October 2022 / Published: 28 October 2022
(This article belongs to the Special Issue Multi-Robot Systems: Theory, Modeling and Applications)

Featured Application

The proposed method in this paper has the potential to solve the task-AGV allocation problem in a complex assembly environment where both multiple-AGV cooperative handling tasks and single-AGV handling tasks exist.

Abstract

An AGV system can be used to transport different-size materials in an assembly line. The hybrid task allocation problem is involved in the assembly line, where both single-AGV tasks and multi-AGV tasks exist. However, there is little research on this problem. The goal of solving this problem is to obtain a task allocation scheme with minimum idle time and maximum system throughput. Since all necessary materials must be delivered to the assembly station before the operation can start, the delivery tasks are not independent of each other in a task group serving the operation. To solve the problem above, a hybrid task allocation method based on a task binding strategy and an improved particle swarm optimization (IPSO) is proposed. Firstly, a mathematical model considering the punctuality of material delivery and the cooperative relationship between tasks is established. Secondly, a task binding strategy and four heuristic rules are devised to improve the quality of randomly- and heuristic-generated individuals in the initial population for model optimization. Thirdly, an IPSO is developed to help the optimization algorithm jump out of local optimums. Finally, a simulation is performed to verify the effectiveness of the proposed methods. The simulation results show that a better scheme can be obtained by our hybrid task allocation method, compared to conventional Genetic Algorithms and PSO algorithms.
Keywords: multi-AGV group; task group; hybrid task allocation; task binding strategy; improved particle swarm optimization multi-AGV group; task group; hybrid task allocation; task binding strategy; improved particle swarm optimization

Share and Cite

MDPI and ACS Style

Hu, Y.; Wu, X.; Zhai, J.; Lou, P.; Qian, X.; Xiao, H. Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line. Appl. Sci. 2022, 12, 10956. https://doi.org/10.3390/app122110956

AMA Style

Hu Y, Wu X, Zhai J, Lou P, Qian X, Xiao H. Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line. Applied Sciences. 2022; 12(21):10956. https://doi.org/10.3390/app122110956

Chicago/Turabian Style

Hu, Ya, Xing Wu, Jingjing Zhai, Peihuang Lou, Xiaoming Qian, and Haining Xiao. 2022. "Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line" Applied Sciences 12, no. 21: 10956. https://doi.org/10.3390/app122110956

APA Style

Hu, Y., Wu, X., Zhai, J., Lou, P., Qian, X., & Xiao, H. (2022). Hybrid Task Allocation of an AGV System for Task Groups of an Assembly Line. Applied Sciences, 12(21), 10956. https://doi.org/10.3390/app122110956

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