A collaborative humanitarian relief chain design for disaster response

•Proposing a novel collaborative humanitarian relief chain design model.•Utilizing information- and resource-sharing as coordination mechanisms.•Developing a Lagrangian relaxation algorithm for solving large-scale problems.•Dealing with disruption risks by a scenario-based robust optimization approa...

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Veröffentlicht in:Computers & industrial engineering 2022-10, Vol.172, p.108643, Article 108643
Hauptverfasser: Shokr, Iman, Jolai, Fariborz, Bozorgi-Amiri, Ali
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Sprache:eng
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Zusammenfassung:•Proposing a novel collaborative humanitarian relief chain design model.•Utilizing information- and resource-sharing as coordination mechanisms.•Developing a Lagrangian relaxation algorithm for solving large-scale problems.•Dealing with disruption risks by a scenario-based robust optimization approach.•Presenting a case study to represent the applicability of the proposed model. Pre- and post-disaster relief operations often involve several humanitarian organizations (HOs) working simultaneously. Balanced and systemic resource-sharing schemes may enable HOs to collaborate effectively and conduct efficient relief operations. In this study, a novel two-stage stochastic model is developed which depends on information- and resource-sharing as coordination mechanisms to ensure proper relief operations while multiple HOs exist in the relief chain. A collaborative humanitarian relief chain (CHRC) consisting of several HOs is designed to make the required decisions on the ways in which relief items are procured, pre-positioned, and distributed pre- and post-disaster. The model is also tweaked to handle potential risks of disruption by an efficient approach. Furthermore, a Lagrangian relaxation algorithm is developed to solve large-scale problems. The performance of the proposed model is tested by being applied to a real-world disaster, namely the 2017 Kermanshah earthquake, in Iran. Several sensitivity analyses are performed to evaluate the applicability of the model and compare the performance of the collaborative decision-making approach proposed in this study to decentralized approaches. Lastly, a number of managerial insights are drawn from the findings.
ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2022.108643