Abstract
The two-sided disassembly line is popular for its high-efficiency disassembly of large-volume end-of-life products. However, in the process of two-sided disassembly, some parts and components need to be disassembled in parallel, and the uncertainty of disassembly time lacks certain research. This paper constructs a fuzzy multiobjective two-sided disassembly line balance problem model based on parallel operation constraint, which aims to reduce the balance loss rate, smoothness index, and energy consumption of disassembly activities. A multiobjective flatworm algorithm based on the Pareto-dominance relationship is developed. To increase the diversity of feasible solutions in the evolution process and accelerate the convergence of Pareto-optimal solutions to prevent the random search of solution space, growth, splitting and regeneration mechanisms are embedded in the algorithm. The working mechanism and efficiency of the multiobjective flatworm algorithm are proved on a series of two-sided disassembly cases, and the excellent performance of the proposed model and algorithm are demonstrated by an actual automobile two-sided disassembly line.
Highlights
With the advancement of manufacturing processes, the lifecycle of products is constantly shortened, and more end-of-life (EOL) products are becoming increasingly unavailable [1]
A mixed-integer programming (MIP) model based on energy efficiency is established for the two-sided disassembly line balancing problem considering parallel operation and fuzzy processing times (TDLBP-POF), which is more realistic than the previous model, and a multiobjective flatworm algorithm (MOFA) is developed to solve the problem
This paper focuses on the multiobjective energy-efficient optimization of the two-sided disassembly line balancing, so the Pareto-optimal mechanism [38] is embedded into FA
Summary
With the advancement of manufacturing processes, the lifecycle of products is constantly shortened, and more end-of-life (EOL) products are becoming increasingly unavailable [1]. Facing a large number of large-volume EOL products to be disassembled, especially for the EOL automobiles and refrigerators, if these two disassembly lines are used, more space, more tools and resources will be occupied, but will lead to a lower disassembly efficiency. Wang proposed the stochastic two-sided partial disassembly line balancing problem and solved it by the discrete flower pollination algorithm [9]. The triangular fuzzy number is introduced into the two-sided disassembly line to simulate the uncertainty of parts disassembly time. A mixed-integer programming (MIP) model based on energy efficiency is established for the two-sided disassembly line balancing problem considering parallel operation and fuzzy processing times (TDLBP-POF), which is more realistic than the previous model, and a multiobjective flatworm algorithm (MOFA) is developed to solve the problem. Conclusions, including directions for further research and exploration, are argued in the last section
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