Multi-objective Discrete Grey Wolf Optimizer for Solving Stochastic Multi-objective Disassembly Sequencing and Line Balancing Problem
Document Type
Conference Proceeding
Publication Date
10-11-2020
Abstract
There is a growing concern in recycling plants for minimizing the negative environmental impacts (such as carbon emissions) of disassembling end-of-life products. Uncertainty caused by their different usage stages exists when disassembling them. In this paper, we propose a stochastic multi-objective disassembly sequencing and line balancing problem based on an AND/OR graph. By considering disassembly failure risk, we construct objectives of maximizing profit and minimizing carbon emission and energy consumption to help sustain economic development. Then, we propose a novel multi-objective discrete grey wolf optimizer to solve it. We show its effectiveness via a product example. The results show the superiority of the proposed algorithm over classical non-dominated sorting genetic algorithm II and multi-objective evolutionary algorithm based on decomposition.
Identifier
85098879001 (Scopus)
ISBN
[9781728185262]
Publication Title
Conference Proceedings IEEE International Conference on Systems Man and Cybernetics
External Full Text Location
https://doi.org/10.1109/SMC42975.2020.9283184
ISSN
1062922X
First Page
682
Last Page
687
Volume
2020-October
Grant
L2019027
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Zhang, Zhi Wei; Guo, Xi Wang; Zhou, Meng Chu; Liu, Shi Xin; and Qi, Liang, "Multi-objective Discrete Grey Wolf Optimizer for Solving Stochastic Multi-objective Disassembly Sequencing and Line Balancing Problem" (2020). Faculty Publications. 4927.
https://digitalcommons.njit.edu/fac_pubs/4927
