| Title: | Coping with shortages caused by disruptive events in automobile supply chains | Authors: | Jiang, Y Shu, J Song, M |
Issue Date: | 2021 | Source: | Naval research logistics, 2021, Early View, p. 1-15, https://doi.org/10.1002/nav.21984 | Abstract: | Unpredictable disruptive events significantly increase the difficulty of the management of automobile supply chains. In this paper, we propose an automobile production planning problem with component chips substitution in a finite planning horizon. The shortage of one chip can be compensated by another chip of the same type with a higher-end feature at an additional cost. Therefore, the automobile manufacturer can divert the on-hand inventory of chips to product lines that are more profitable in the event of shortages caused by supply chain disruptions. To cope with this, we propose a max-min robust optimization model that captures the uncertain supplies of chips. We show that the robust model has a mixed-integer programming equivalence that can be solved by a commercial IP solver directly. We compare the max-min robust model with the corresponding deterministic and two-stage stochastic models for the same problem through extensive numerical experiments. The computational results show that the max-min robust model outperforms the other two models in terms of the average and worst-case profits. | Keywords: | Automobile supply chain Component substitution Two-stage model |
Publisher: | John Wiley & Sons | Journal: | Naval research logistics | ISSN: | 0894-069X | EISSN: | 1520-6750 | DOI: | 10.1002/nav.21984 |
| Appears in Collections: | Journal/Magazine Article |
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