TY - GEN
T1 - Solving the Circular Disassembly Line Balancing Problem in Shifts Considering Human Learning Effect Based on IMPALA Algorithm
AU - Zhang, Haitao
AU - Guo, Xiwang
AU - Wang, Jiacun
AU - Qin, Shujin
AU - Hu, Bin
AU - Qi, Liang
AU - Chen, Siqi
AU - Wang, Jun
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Product disassembly is significant for recycling scrapped products and reducing environmental pollution and resource waste. The recovery, reuse, and recycling of industrial products is crucial in modern industry. Manual disassembly efficiency significantly impacts the disassembly line's overall effectiveness, especially workers' skill level and learning efficiency. This paper proposes a multi-period personnel scheduling problem that considers worker learning effects. A mixed integer programming model for the disassembly balance problem was established to maximize disassembly profit. This problem is solved using a new reinforcement learning algorithm, the importance-weighted actor-learner architecture (IMPALA). The correctness and effectiveness of the proposed algorithm are verified through comparative experiments with the famous IBM optimizer CPLEX and some popular peer algorithms.
AB - Product disassembly is significant for recycling scrapped products and reducing environmental pollution and resource waste. The recovery, reuse, and recycling of industrial products is crucial in modern industry. Manual disassembly efficiency significantly impacts the disassembly line's overall effectiveness, especially workers' skill level and learning efficiency. This paper proposes a multi-period personnel scheduling problem that considers worker learning effects. A mixed integer programming model for the disassembly balance problem was established to maximize disassembly profit. This problem is solved using a new reinforcement learning algorithm, the importance-weighted actor-learner architecture (IMPALA). The correctness and effectiveness of the proposed algorithm are verified through comparative experiments with the famous IBM optimizer CPLEX and some popular peer algorithms.
KW - circular layout
KW - Disassembly line balancing problem
KW - IMPALA algorithm
KW - learning effect
KW - multi-skilled workers
KW - multiple periods
UR - https://www.scopus.com/pages/publications/105033147736
U2 - 10.1109/SMC58881.2025.11342960
DO - 10.1109/SMC58881.2025.11342960
M3 - Conference contribution
AN - SCOPUS:105033147736
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 5839
EP - 5844
BT - 2025 IEEE International Conference on Systems, Man, and Cybernetics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2025
Y2 - 5 October 2025 through 8 October 2025
ER -