Energy‐efficient optimization of two‐sided disassembly line balance considering parallel operation and uncertain using multiobjective flatworm algorithm

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.