Humanitarian relief supply network design: Expander graph based approach and a case study of 2013 Flood in Northeast China

Jia Shu, Wenya Lv and Qing Na

Transportation Research Part E: Logistics and Transportation Review, 2021, vol. 146, issue C

Abstract: The frequent occurrence and catastrophic consequence of natural disasters have made it important to design an appropriate humanitarian relief supply network that can provide (cost-) effective and timely rescue for affected people. This paper presents a humanitarian relief supply network design model for large-scale natural disasters such as flood and hurricane. The model is constructed through the adoption of a Ψ-expander structure which is a variant of expander graph and a sparse yet highly connected structure with good flexibility. The Ψ-expander structure guarantees that either the network can satisfy the total demand among affected areas or utilize at least Ψ proportion of the total pre-positioned relief supply. The model optimizes the decisions of emergency facility location and relief supply pre-positioning simultaneously under uncertain demand in each affected area. The objective is to minimize the total cost of fixed location and relief supply pre-positioning. The model is cast as a nonlinear integer program with an exponential size of the Ψ-expander constraints. We address it using a cutting-plane approach. We also analyze the complexity of the separation problem that must be solved in each iteration of the cutting-plane approach and prove that it is NP-hard. A case study based on the 2013 Flood in Northeast China is presented to verify the performance of the model. Computational results demonstrate that the model is able to design a humanitarian relief supply network with a high demand fill rate effectively.

Keywords: Disaster operations management; Emergency facility location; Relief supply pre-positioning; Expander graph (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.tre.2020.102178

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