A new optimization algorithm for assembly sequence planning was designed to address the issues of low efficiency and poor convergence in traditional optimization algorithms. This article applies an optimization algorithm based on the bald eagle optimization algorithm to the optimization of assembly sequence planning. By extracting the connection relationships and information of experimental components, a disassembly matrix was derived using disassembly methods. The interference and dependency relationships between various components of the experimental object during the disassembly process were described, and a priority relationship diagram of disassembly operation tasks was obtained. A fitness function for achieving multi-objective optimization was constructed by combining four evaluation indicators: frequency of replacing disassembly tools, frequency of replacing disassembly directions, weighted disassembly time, and recycling efficiency.
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Luo et al. (2024) studied this question.
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