TY - GEN
T1 - Modeling and Solution of Multi-objective Parallel Disassembly Line Balancing Problem Considering Human Factors
AU - Zhang, Zhiwei
AU - Guo, Xi Wang
AU - Wang, Jiacun
AU - Qin, Shujin
AU - Qi, Liang
AU - Tang, Ying
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Disassembly is of significant importance in maintenance, remanufacturing, and recycling, as it promotes sustainable development and resource utilization. However, due to the rapid advancement of production automation, designers often overlook the fact that manual operations offer greater flexibility and employee satisfaction during task execution, thereby impacting production efficiency and effectiveness. Therefore, considering human factors in disassembly line balancing problems holds significant research significance. In this work, we investigate the multi-objective parallel disassembly line balancing problem, taking into account factors such as worker fatigue. We establish a mathematical model that incorporates worker fatigue and employ the Pareto Envelope based Selection Algorithm II (PESA-II) for solving the proposed problem. Comparative analysis is conducted, comparing the results with other algorithms, including Pareto Archived Evolution Strategy (PESA), Carnivorous plant algorithm (CPA), Fruit Fly Optimization Algorithm (FOA), and Multivariate Singular Spectrum Analysis (MSSA), based on multiple sets of experimental cases to demonstrate the outstanding performance of PESA-II across various metrics.
AB - Disassembly is of significant importance in maintenance, remanufacturing, and recycling, as it promotes sustainable development and resource utilization. However, due to the rapid advancement of production automation, designers often overlook the fact that manual operations offer greater flexibility and employee satisfaction during task execution, thereby impacting production efficiency and effectiveness. Therefore, considering human factors in disassembly line balancing problems holds significant research significance. In this work, we investigate the multi-objective parallel disassembly line balancing problem, taking into account factors such as worker fatigue. We establish a mathematical model that incorporates worker fatigue and employ the Pareto Envelope based Selection Algorithm II (PESA-II) for solving the proposed problem. Comparative analysis is conducted, comparing the results with other algorithms, including Pareto Archived Evolution Strategy (PESA), Carnivorous plant algorithm (CPA), Fruit Fly Optimization Algorithm (FOA), and Multivariate Singular Spectrum Analysis (MSSA), based on multiple sets of experimental cases to demonstrate the outstanding performance of PESA-II across various metrics.
UR - http://www.scopus.com/inward/record.url?scp=85179622456&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179622456&partnerID=8YFLogxK
U2 - 10.1109/ICNSC58704.2023.10319009
DO - 10.1109/ICNSC58704.2023.10319009
M3 - Conference contribution
AN - SCOPUS:85179622456
T3 - ICNSC 2023 - 20th IEEE International Conference on Networking, Sensing and Control
BT - ICNSC 2023 - 20th IEEE International Conference on Networking, Sensing and Control
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Networking, Sensing and Control, ICNSC 2023
Y2 - 25 October 2023 through 27 October 2023
ER -