An Improved Discrete Bat Algorithm for Multi-Objective Partial Parallel Disassembly Line Balancing Problem

Qi Zhang, Yang Xing, Man Yao, Jiacun Wang, Xiwang Guo, Shujin Qin, Liang Qi () and Fuguang Huang
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Qi Zhang: College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China
Yang Xing: College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China
Man Yao: School of Basic Medicine, He University, Shenyang 110163, China
Jiacun Wang: Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764, USA
Xiwang Guo: College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China
Shujin Qin: College of Economics and Management, Shangqiu Normal University, Shangqiu 476000, China
Liang Qi: Department of Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China
Fuguang Huang: College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China

Mathematics, 2024, vol. 12, issue 5, 1-22

Abstract: Product disassembly is an effective means of waste recycling and reutilization that has received much attention recently. In terms of disassembly efficiency, the number of disassembly skills possessed by workers plays a crucial role in improving disassembly efficiency. Therefore, in order to effectively and reasonably disassemble discarded products, this paper proposes a partial parallel disassembly line balancing problem (PP-DLBP) that takes into account the number of worker skills. In this paper, the disassembly tasks and the disassembly relationships between components are described using AND–OR graphs. In this paper, a multi-objective optimization model is established aiming to maximize the net profit of disassembly and minimize the number of skills for the workers. Based on the bat algorithm (BA), we propose an improved discrete bat algorithm (IDBA), which involves designing adaptive composite optimization operators to replace the original continuous formula expressions and applying them to solve the PP-DLBP. To demonstrate the advantages of IDBA, we compares it with NSGA-II, NSGA-III, SPEA-II, ESPEA, and MOEA/D. Experimental results show that IDBA outperforms the other five algorithms in real disassembly cases and exhibits high efficiency.

Keywords: parallel disassembly lines; discrete bat algorithm; multi-objective optimization; disassembly skills (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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