TY - JOUR
T1 - Hybrid Disassembly Line Balancing of Multi-Factory Remanufacturing Process Considering Workers with Government Benefits
AU - Niu, Xiaoyu
AU - Guo, Xiwang
AU - Liu, Peisheng
AU - Wang, Jiacun
AU - Qin, Shujin
AU - Qi, Liang
AU - Hu, Bin
AU - Ji, Yingjun
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/3
Y1 - 2025/3
N2 - Optimizing multi-factory remanufacturing systems with social welfare considerations presents critical challenges in task allocation and process coordination. This study addresses this gap by proposing a hybrid disassembly line balancing and multi-factory remanufacturing process optimization problem, considering workers with government benefits. A mixed-integer programming model is formulated to maximize profit, and its correctness is verified using the CPLEX solver. Furthermore, a discrete zebra optimization algorithm is proposed to solve the model, integrating a survival-of-the-fittest strategy to improve its optimization capabilities. The effectiveness and convergence of the algorithm are demonstrated through experiments on disassembly cases, with comparisons made to six peer algorithms and CPLEX. The experimental results highlight the importance of this research in improving resource utilization efficiency, reducing environmental impacts, and promoting sustainable development.
AB - Optimizing multi-factory remanufacturing systems with social welfare considerations presents critical challenges in task allocation and process coordination. This study addresses this gap by proposing a hybrid disassembly line balancing and multi-factory remanufacturing process optimization problem, considering workers with government benefits. A mixed-integer programming model is formulated to maximize profit, and its correctness is verified using the CPLEX solver. Furthermore, a discrete zebra optimization algorithm is proposed to solve the model, integrating a survival-of-the-fittest strategy to improve its optimization capabilities. The effectiveness and convergence of the algorithm are demonstrated through experiments on disassembly cases, with comparisons made to six peer algorithms and CPLEX. The experimental results highlight the importance of this research in improving resource utilization efficiency, reducing environmental impacts, and promoting sustainable development.
KW - hybrid disassembly line balancing
KW - multi-factory remanufacturing process optimization
KW - workers with government benefits
KW - zebra optimization algorithm
UR - http://www.scopus.com/inward/record.url?scp=86000666375&partnerID=8YFLogxK
U2 - 10.3390/math13050880
DO - 10.3390/math13050880
M3 - Article
AN - SCOPUS:86000666375
SN - 2227-7390
VL - 13
JO - Mathematics
JF - Mathematics
IS - 5
M1 - 880
ER -