Review of Research on Human-Machine Collaboration in Disassembly Line Balancing Problem

Abstract

This paper aims to explore the research on the human-machine collaboration in the disassembly line balancing problem, in response to the importance of dismantling and reusing waste products. Human-machine collaboration in disassembly, as a method combining human intelligence with machine power, has the potential to enhance disassembly efficiency, reduce resource wastage, and minimize human exposure to hazards. However, due to the NP-hard nature of this problem, traditional exact algorithms perform poorly when facing large-scale and complex problems. Therefore, this paper explores the application of intelligent algorithms such as genetic algorithms, wolf pack algorithms, etc., and proposes novel and efficient solutions to the human-machine collaboration in disassembly line balancing problem. Additionally, to address the challenge of the large-scale problem state space, this paper also discusses the potential application of emerging technologies such as reinforcement learning. Through these studies, this review aims to promote the development of the remanufacturing industry and facilitate resource utilization and environmental protection.