期刊
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
卷 244, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ijpe.2021.108370
关键词
Maintenance logistics network; Collaboration; Repairable components; Two-stage robust optimization; Monte-Carlo simulation
资金
- Canadian Natural Science and Engineering Research Council [RGPIN/04 803-2017, RGPIN/084 141-2015, B2X/288 888-2020]
This study proposes a two-stage robust optimization model for collaborative design and planning of maintenance networks under demand uncertainty, aiming to minimize the cost of late deliveries. By sharing resources among different maintenance facilities, delays in the delivery of repaired devices can be reduced effectively.
Maintenance service providers to advanced technical devices are confronted with uncertain demand, high cost of components, and the need for certified operators. Collaboration in terms of sharing scarce resources among different facilities in a maintenance logistics network is expected to reduce the delays in the delivery of repaired devices. This study proposes a two-stage robust optimization model for collaborative design and planning of maintenance networks under demand uncertainty. The goal of this model is to determine the optimal allocation of customers to each maintenance center along with the initial stock level of different components in each facility so as to minimize the cost of late deliveries under worst-case demand scenarios. Component and operator sharing strategies are proposed as the recourse actions in this model to hedge against the demand surge. The proposed approach is compared with a deterministic model by the aid of Monte-Carlo simulation on several test instances inspired by a real case study. Our numerical experiments demonstrate the significance of adopting the proposed collaborative mechanisms among maintenance facilities in terms of cost reduction, especially when the demand fluctuation is relatively high.
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