| Autor: |
Qidong Yin, Xiaochuan Luo, Julien Hohenstein |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Journal of Mathematics, Vol 2021 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2314-4785 |
| DOI: |
10.1155/2021/4196228 |
| Popis: |
Two-sided assembly lines are widely used in the large-size product manufacturing industry, especially for automotive assembly production. Balancing the assembly line is significant for assembly process planning and assembly production. In this study, we develop a novel and exact method to optimize the two-sided assembly line balancing problem with zoning constraints (TALBz), in which the aim is to minimize the number of mated-stations considering the task restrictions. A mixed-integer programming model is employed to exactly describe the TALBz problem. To strengthen the computational efficiency, we apply Dantzig–Wolfe decomposition to reformulate the TALBz problem. We further propose a branch-and-price (B&P) algorithm that integrates the column generation approach into a branch-and-bound frame. Both the benchmark datasets with zoning constraints and without zoning constraints are tested to evaluate the performance of the B&P algorithm. The numerical results show that our proposed approach can obtain optimal solutions efficiently on most cases. In addition, experiments on the real-world datasets originating from passenger vehicle assembly lines are conducted. The proposed B&P algorithm shows its advantage in tackling practical problems with the task restrictions. This developed methodology therefore provides insight for solving large-scale TALBz problems in practice. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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