Mathematics (Mar 2024)

An Improved Moth-Flame Algorithm for Human–Robot Collaborative Parallel Disassembly Line Balancing Problem

  • Qi Zhang,
  • Bin Xu,
  • Man Yao,
  • Jiacun Wang,
  • Xiwang Guo,
  • Shujin Qin,
  • Liang Qi,
  • Fayang Lu

DOI
https://doi.org/10.3390/math12060816
Journal volume & issue
Vol. 12, no. 6
p. 816

Abstract

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In the context of sustainable development strategies, the recycling of discarded products has become increasingly important with the development of electronic technology. Choosing the human–robot collaborative disassembly mode is the key to optimizing the disassembly process and ensuring maximum efficiency and benefits. To solve the problem of human–robot cooperative parallel dismantling line balance, a mixed integer programming model is established and verified by CPLEX. An improved Moth-Flame Optimization (IMFO) algorithm is proposed to speed up convergence and optimize the disassembly process of various products. The effectiveness of IMFO is evaluated through multiple cases and compared with other heuristics. The results of these comparisons can provide insight into whether IMFO is the most appropriate algorithm for the problem presented.

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