Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures

Gongdan Xu, Zhiwei Zhang, Zhiwu Li (), Xiwang Guo, Liang Qi and Xianzhao Liu
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Gongdan Xu: Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau 999078, China
Zhiwei Zhang: College of Computer and Communication Engineering, Liaoning Petrochemical University, Fushun 113001, China
Zhiwu Li: Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau 999078, China
Xiwang Guo: College of Computer and Communication Engineering, Liaoning Petrochemical University, Fushun 113001, China
Liang Qi: Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China
Xianzhao Liu: Hitachi Building Technology (Guangzhou) Co., Ltd., Guangzhou 510670, China

Mathematics, 2023, vol. 11, issue 6, 1-22

Abstract: Robots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) product disassembly efficiency. Most of the current research on disassembly line balancing problems focuses on decomposing one product. More than one product can be disassembled concurrently, which can further improve the efficiency. Moreover, uncertainty such as the depreciation of EOL products, may result in disassembly failure. In this research, a stochastic multi-product robotic disassembly line balancing model is established using an AND/OR graph. It takes the precedence relationship, cycle constraint, and disassembly failure into consideration to maximize the profit and minimize the energy consumption for disassembling multiple products. A Pareto-improved multi-objective brainstorming optimization algorithm combined with stochastic simulation is proposed to solve the problem. Furthermore, by conducting experiments on some real cases and comparing with four state-of-the-art multi-objective optimization algorithms, i.e., the multi-objective discrete gray wolf optimizer, artificial bee colony algorithm, nondominated sorting genetic algorithm II, and multi-objective evolutionary algorithm based on decomposition, this paper validates its excellent performance in solving the concerned problem.

Keywords: disassembly failure; machine learning; multiple product disassembly; robotic disassembly line balancing problem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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