Discrete Fruit Fly Optimization Algorithm for Disassembly Line Balancing Problems by Considering Human Worker's Learning Effect
Document Type
Conference Proceeding
Publication Date
1-1-2022
Abstract
The recycling of discarded products is an integral part of resource utilization. A disassembly line balancing problem (DLBP) concerns the recycling and remanufacturing process of end-of-life (EOL) products. Disassembly time is affected by many factors, e.g., the precedence relationships among disassembly tasks, and the skills and learning abilities of disassembly workers. In this paper, we use Petri nets to specify a disassembly process and establish a mixed integer programming model to describe DLBP that considers the learning effect of human workers. We then propose a discrete fruit fly optimization algorithm to solve the proposed problem. By comparing its experimental results with other intelligent optimization algorithms', its efficiency is verified.
Identifier
85144634945 (Scopus)
ISBN
[9781665498876]
Publication Title
2022 Australian and New Zealand Control Conference Anzcc 2022
External Full Text Location
https://doi.org/10.1109/ANZCC56036.2022.9966961
First Page
201
Last Page
206
Grant
61903229
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Wang, Jianping; Guo, Xiwang; Zhou, Mengchu; Wang, Jiacun; Qin, Shujin; and Qi, Liang, "Discrete Fruit Fly Optimization Algorithm for Disassembly Line Balancing Problems by Considering Human Worker's Learning Effect" (2022). Faculty Publications. 3516.
https://digitalcommons.njit.edu/fac_pubs/3516
