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Volume 12
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Article

An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation

by
Shujin Qin
1,
Xinkai Xie
2,
Jiacun Wang
3,
Xiwang Guo
2,
Liang Qi
4,*,
Weibiao Cai
2,
Ying Tang
5 and
Qurra Tul Ann Talukder
4
1
College of Economics and Management, Shangqiu Normal University, Shangqiu 476000, China
2
College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China
3
Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764, USA
4
Department of Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China
5
College of Electrical and Computer Engineering, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Mathematics 2024, 12(6), 836; https://doi.org/10.3390/math12060836
Submission received: 14 January 2024 / Revised: 7 March 2024 / Accepted: 8 March 2024 / Published: 12 March 2024
(This article belongs to the Special Issue Ensemble Evolutionary Algorithms and Machine Learning for Solving Complex Optimization and Scheduling Problems)
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Abstract

The growing emphasis on ecological preservation and natural resource conservation has significantly advanced resource recycling, facilitating the realization of a sustainable green economy. Essential to resource recycling is the pivotal stage of disassembly, wherein the efficacy of disassembly tools plays a critical role. This work investigates the impact of disassembly tools on disassembly duration and formulates a mathematical model aimed at minimizing workstation cycle time. To solve this model, we employ an optimized advantage actor-critic algorithm within reinforcement learning. Furthermore, it utilizes the CPLEX solver to validate the model’s accuracy. The experimental results obtained from CPLEX not only confirm the algorithm’s viability but also enable a comparative analysis against both the original advantage actor-critic algorithm and the actor-critic algorithm. This comparative work verifies the superiority of the proposed algorithm.
Keywords: disassembly line balancing; tool deterioration; reinforcement learning; advantage actor-critic algorithm disassembly line balancing; tool deterioration; reinforcement learning; advantage actor-critic algorithm

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MDPI and ACS Style

Qin, S.; Xie, X.; Wang, J.; Guo, X.; Qi, L.; Cai, W.; Tang, Y.; Talukder, Q.T.A. An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation. Mathematics 2024, 12, 836. https://doi.org/10.3390/math12060836

AMA Style

Qin S, Xie X, Wang J, Guo X, Qi L, Cai W, Tang Y, Talukder QTA. An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation. Mathematics. 2024; 12(6):836. https://doi.org/10.3390/math12060836

Chicago/Turabian Style

Qin, Shujin, Xinkai Xie, Jiacun Wang, Xiwang Guo, Liang Qi, Weibiao Cai, Ying Tang, and Qurra Tul Ann Talukder. 2024. "An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation" Mathematics 12, no. 6: 836. https://doi.org/10.3390/math12060836

APA Style

Qin, S., Xie, X., Wang, J., Guo, X., Qi, L., Cai, W., Tang, Y., & Talukder, Q. T. A. (2024). An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation. Mathematics, 12(6), 836. https://doi.org/10.3390/math12060836

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