Bat optimizer for stochastic multiple-objective disassembly line balancing problem subject to disassembly failure cost

Fuguang Huang; Peisheng Liu; Xiwang Guo; Jiacun Wang; Liang Qi; Shujin Qin; Gongdan Xu

doi:10.1117/12.2626895

14 February 2022 Bat optimizer for stochastic multiple-objective disassembly line balancing problem subject to disassembly failure cost

Fuguang Huang, Peisheng Liu, Xiwang Guo, Jiacun Wang, Liang Qi, Shujin Qin, Gongdan Xu

Author Affiliations +

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 121611M (2022) https://doi.org/10.1117/12.2626895
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

Disassembly systems play an important role in the remanufacturing processes. It has been widely used to systematically disassemble valuable and reusable parts and raw materials from wasted or end-of-life products through a series of operations. In this work, a disassembly line balancing model is established based on an AND/OR graph. It takes precedence relation, cycle time restriction, failure risk, and time uncertainty into consideration and aims to maximize the dismantling profit and minimize the energy consumption. Then, a multi-objective discrete bat optimizer based on Pareto rules is designed. A precedence preserving crossover operator, a single point mutation operator, and a 2-optimization operator are used in the search stage. To speed up the convergence, this paper proposes an elite strategy to maintain the non-dominate solutions in the external files and verify the effectiveness of the algorithm in solving the disassembly line balancing problem by comparing it with the current popular multi-objective optimization algorithm.

Citation Download Citation

Fuguang Huang, Peisheng Liu, Xiwang Guo, Jiacun Wang, Liang Qi, Shujin Qin, and Gongdan Xu "Bat optimizer for stochastic multiple-objective disassembly line balancing problem subject to disassembly failure cost", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 121611M (14 February 2022); https://doi.org/10.1117/12.2626895

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