- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | LUO Yabo, ZHOU Xiangyu, ZHANG Feng, LI Cunrong. Multi-Skilled Multi-Manned Assembly Line Rebalancing Problem Based on Two-Stage Algorithm[J]. Journal of Southwest Jiaotong University, 2025, 60(6): 1611-1622. doi: 10.3969/j.issn.0258-2724.20240002
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To improve the production efficiency and flexibility of assembly lines, based on the consideration of multi-manned stations and variations in worker proficiency, an analysis and design of the rebalancing problem for multi-skilled multi-manned assembly lines and corresponding solution algorithms have been conducted. Firstly, the concepts of worker proficiency and comprehensive influence coefficient are proposed to quantify the differences among workers and the effects of multi-manned stations, and a multi-objective optimization model is established accordingly. Secondly, the ε-constraint method and a two-stage algorithm combining greedy heuristic and neighborhood search are proposed to solve problems of different scales. Finally, ablation study and algorithm comparison experiments are designed for validation. The research results show that in the testing of small-scale problems, the solutions of the model only differ by 0.3% in one data point, demonstrating the accuracy of the model. In the ablation study, abandoning any algorithm strategy leads to worse results, indicating the effectiveness of each strategy. Furthermore, in the comparison of large-scale problems, the proposed algorithm exhibits significant advantages over the classical multi-objective optimization algorithms NSGA-Ⅱ and MOEA/D in most cases, thus proving the superiority of the proposed algorithm in solving this problem.
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