Balancing Human-robot Collaborative Disassembly Line by Using Dingo Optimization Algorithm
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
Disassembling and recycling scrapped products play important roles in effectively reducing environmental pollution and improving resource sustainability. A multi-product human-robot collaborative disassembly-line-balancing problem (MHDP) arises from doing so and represents an important yet to be solved in the remanufacturing field. This work explores how to use optimization algorithms to schedule tasks between humans and robots to maximize remanufacturing profit in human-robot collaboration contexts. Specifically, we investigate MHDP and develop a mixed integer programming model considering various system constraints. We propose a dingo optimization algorithm that simulates wild dogs' social hierarchy and chasing processes to solve MHDP. We compare the proposed algorithm with an exact solution finder, i.e., IBM CPLEX and a well-known intelligent optimization method, i.e., Genetic Algorithm to show its competitive performance in terms of solution accuracy and efficiency.
Identifier
85197388446 (Scopus)
ISBN
[9798350315790]
Publication Title
2024 IEEE 4th International Conference on Human-Machine Systems, ICHMS 2024
External Full Text Location
https://doi.org/10.1109/ICHMS59971.2024.10555664
Recommended Citation
Guo, Xiwang; Zhou, Liangbo; Zhou, Mengchu; Wang, Weitian; Wang, Jiacun; and Qi, Liang, "Balancing Human-robot Collaborative Disassembly Line by Using Dingo Optimization Algorithm" (2024). Faculty Publications. 965.
https://digitalcommons.njit.edu/fac_pubs/965
