Mathematics (Sep 2024)

Unified Modeling and Multi-Objective Optimization for Disassembly Line Balancing with Distinct Station Configurations

  • Tao Yin,
  • Yuanzhi Wang,
  • Shixi Cai,
  • Yuxun Zhang,
  • Jianyu Long

DOI
https://doi.org/10.3390/math12172734
Journal volume & issue
Vol. 12, no. 17
p. 2734

Abstract

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Disassembly line balancing (DLB) is a crucial optimization item in the recycling and remanufacturing of waste products. Considering the variations in the number of operators assigned to each station, this study investigates DLBs with six distinct station configurations: single-manned, multi-manned, single-robotic, multi-robotic, single-manned–robotic, and multi-manned–robotic setups. First, a unified mixed-integer programming (MIP) model is established for Type-I DLBs with each configuration to minimize four objectives: the number of stations, the number of operators, the total disassembly time, and the idle balancing index. To obtain more solutions, a novel bi-metric is proposed to replace the quadratic idle balancing index and is used in lexicographic optimization. Subsequently, based on the unified Type-I models, a unified MIP model for Type-II DLBs is established to minimize the cycle time, the number of operators, the total disassembly time, and the idle balancing index. Finally, the correctness of the established unified models and the effectiveness of the proposed bi-metric are verified by solving two disassembly cases of lighters and hairdryers, which further shows that the mathematical integration method of unified modeling has significant theoretical value for the multi-objective optimization of the DLBs with six distinct station configurations.

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