TY - GEN
T1 - Multi-Objective Multi-Verse Optimizer for Multi-Product Partial U-Shaped Disassembly Line Balancing Problem
AU - Zhang, Shancheng
AU - Guo, Laide
AU - Guo, Xiwang
AU - Liu, Shixin
AU - Qi, Liang
AU - Qin, Shujin
AU - Tang, Ying
AU - Zhao, Ziyan
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported in part by Liaoning Province Education Department Scientific Research Foundation of China under Grant No. L2019027; LiaoNing Revitalization Talents Program under Grant No. XLYC1907166; The Natural Science Foundation of Shandong Province under Grant ZR2019BF004; National Natural Science Foundation of China (61573089); Archival Science and Technology Project of Liaoning Province, No.2021-B-004.References; Education Ministry Humanities and Social Science Research Youth Fund Project of China under grant 20YJCZH159.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The development of industry and technology promotes the acceleration of product replacement, and generate a large number of end-of-life products. Meanwhile, robots also play a significant role in disassembly. This paper proposes a scheme to solve a U-shaped disassembly line balancing problem with robots. A mathematical model for maximizing profits and minimizing carbon emissions is established. Then, the paper proposes an improved Multi-Objective Multi-Verse Optimizer (MOMVO) to solve the problem. Taking the disassembly of ballpoint pen and hammer drill as examples, our method is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), and Multi-Objective Cellular Genetic Algorithm (MOCGA). Comparison indexes include Inverted Generational Distance+ (IGD+) and hypervolume epsilon metric. The experimental results show that the MOMVO algorithm performs better than others on the U-shaped and robotic disassembly line.
AB - The development of industry and technology promotes the acceleration of product replacement, and generate a large number of end-of-life products. Meanwhile, robots also play a significant role in disassembly. This paper proposes a scheme to solve a U-shaped disassembly line balancing problem with robots. A mathematical model for maximizing profits and minimizing carbon emissions is established. Then, the paper proposes an improved Multi-Objective Multi-Verse Optimizer (MOMVO) to solve the problem. Taking the disassembly of ballpoint pen and hammer drill as examples, our method is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), and Multi-Objective Cellular Genetic Algorithm (MOCGA). Comparison indexes include Inverted Generational Distance+ (IGD+) and hypervolume epsilon metric. The experimental results show that the MOMVO algorithm performs better than others on the U-shaped and robotic disassembly line.
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U2 - 10.1109/ICNSC52481.2021.9702256
DO - 10.1109/ICNSC52481.2021.9702256
M3 - Conference contribution
AN - SCOPUS:85126642254
T3 - ICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control: Industry 4.0 and AI
BT - ICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021
Y2 - 3 December 2021 through 5 December 2021
ER -