Grey Wolf Algorithm for Human-Robot Collaborative Disassembly Line Balancing Problem Subject to Dangerous Components

Chong Li, Xiwang Guo, Jiacun Wang, Shujin Qin, Liang Qi, Ying Tang
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引用次数: 1

Abstract

Disassembly is a critical remanufacturing process to obtain reusable components from discarded products. Due to the limitation of disassembly by humans or robots alone, the human-robot collaborative disassembly method is used to obtain components. Three types of components are considered in this paper: dangerous, delicate and normal. Robots disassemble dangerous components, humans disassemble delicate components, and both humans and robots can disassemble normal components. A mathematical model that maximizes disassembly profit is established. An improved gray wolf optimizer algorithm to solve the single-product disassembly line balancing problem is proposed. The algorithm is compared with the migratory bird optimization algorithm and the brain storming optimization algorithm to test its performance. Experimental results show that the proposed algorithm has a faster convergence speed.
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考虑危险部件的人机协同拆解线平衡问题的灰狼算法
拆卸是从废弃产品中获得可重复使用部件的关键再制造过程。由于人工或机器人单独拆卸的局限性,采用人机协同拆卸的方法获取部件。本文考虑了三种类型的组件:危险、微妙和正常。机器人拆卸危险部件,人类拆卸脆弱部件,人和机器人都可以拆卸正常部件。建立了使拆解利润最大化的数学模型。提出了一种改进的灰狼优化算法来解决单产品拆解线平衡问题。将该算法与候鸟优化算法和头脑风暴优化算法进行比较,测试其性能。实验结果表明,该算法具有较快的收敛速度。
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