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A hybrid many-objective competitive swarm optimization algorithm for large-scale multirobot task allocation problem

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Abstract

Large-scale multi-robot task allocation (MRTA) problem is an important part of intelligent logistics scheduling. And the load capacity of robot and picking station are important factors affecting the MRTA problem. In this paper, the MRTA problem is built as a many-objective optimization model with four objectives, which takes the load capacity of single robot, single picking station, all robots and all picking stations into account. To solve the model, a hybrid many-objective competitive swarm optimization (HMaCSO) algorithm is designed. The novel selection method employing two different measurement mechanisms will form the mating selection operation. Then the population will be updated by employing the competitive swarm optimization strategy. Meanwhile, the environment selection will play a role in choosing the excellent solution. To prove the superiority of our approach, there are two series of experiments are carried out. On the one hand, our approach is compared with other five famous many-objective algorithms on benchmark problem. On the other hand, the involved algorithms are applied in solving large-scale MRTA problem. Simulation results prove that the performance of our approach is superior than other algorithms.

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Acknowledgements

This paper is supported by Humanity and Social Science Research of Ministry of Education (20YJCZH200), Beijing Intelligent Logistics System Collaborative Innovation Center Open Topic (No. BILSCIC-2019KF- 05), General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China (No. KM201810037002), Grass-roots Academic Team Building Project of Beijing Wuzi University (No. 2019XJJCTD04), Beijing Youth Top-notch Talent Plan of High-Creation Plan (No. 2017000026833ZK25), Canal Plan-Leading Talent Project of Beijing Tongzhou District (No. YHLB2017038).

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Authors and Affiliations

  1. School of Information, Beijing Wuzi University, Beijing, 101149, China

    Fei Xue, Tingting Dong, Siqing You, Yan Liu, Hengliang Tang, Lei Chen, Xi Yang & Juntao Li

  2. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Tingting Dong

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  1. Fei Xue
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Xue, F., Dong, T., You, S. et al. A hybrid many-objective competitive swarm optimization algorithm for large-scale multirobot task allocation problem. Int. J. Mach. Learn. & Cyber. 12, 943–957 (2021). https://doi.org/10.1007/s13042-020-01213-4

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