Hybrid particle swarm optimization algorithms for cost-oriented robotic assembly line balancing problems
Robotic Intelligence and Automation
ISSN: 2754-6969
Article publication date: 27 June 2023
Issue publication date: 21 August 2023
Abstract
Purpose
The cost-oriented robotic assembly line balancing problem (cRALBP) has practical importance in real-life manufacturing scenarios. However, only a few studies tackle the cRALBP using exact methods or metaheuristics. This paper aims to propose a hybrid particle swarm optimization (PSO) combined with dynamic programming (DPPSO) to solve cRALBP type-I.
Design/methodology/approach
Two different encoding schemes are presented for comparison. In the frequently used Scheme 1, a full encoding of task permutations and robot allocations is adopted, and a relatively large search space is generated. DPSO1 and DPSO2 with the full encoding scheme are developed. To reduce the search space and concern promising solution regions, in Scheme 2, only task permutations are encoded, and DP is used to obtain the optimal robot sequence for a given task permutation in a polynomial time. DPPSO is proposed.
Findings
A set of instances is generated, and the numerical experiments indicate that DPPSO achieves a tradeoff between solution quality and computation time and outperforms existing algorithms in solution quality.
Originality/value
The contributions of this paper are three aspects. First, two different schemes of encoding are presented, and three PSO algorithms are developed for the purpose of comparison. Second, a novel updating mechanism of discrete PSO is adjusted to generate feasible task permutations for cRALBP. Finally, a set of instances is generated based on two cost parameters, then the performances of algorithms are systematically compared.
Keywords
Acknowledgements
Funding: This paper is supported by the National Natural Science Foundation of China under grant No. 51575108 and the Open Projects of State Key Lab of Digital Manufacturing Equipment & Technology (No. DMETKF2021009).
Ethics approval and consent to participate Not applicable.
Consent for publication: All authors have checked the manuscript and have agreed to the submission.
Competing interests: The authors declare that they have no conflict of interest.
Citation
Zhang, C., Dou, J., Wang, S. and Wang, P. (2023), "Hybrid particle swarm optimization algorithms for cost-oriented robotic assembly line balancing problems", Robotic Intelligence and Automation, Vol. 43 No. 4, pp. 420-430. https://doi.org/10.1108/RIA-07-2022-0178
Publisher
:Emerald Publishing Limited
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