Pre- and Post-Disaster Allocation Strategies of Relief Items in the Presence of Resilience

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Abstract

Pre-disaster and post-disaster allocation strategies are widely investigated as the single optimization problem in humanitarian supply chain management, while integrated decisions including the above two problems are seldom discussed in the existing literature. Here, this paper proposes a mixed-integer programming model to determine these decisions, including the location of central warehouses and emergency storage points and the quantities of relief items pre-deployed and distributed. Specially, two preferences regarding costs and cost-resilience are considered, and a comparison of two models concerning the above preferences is performed. The results are as follows: (i) When the impact of disasters is at a relatively low or moderate level, the cost-oriented model can reduce the government’s financial burden and increase the coverage of relief items. However, when the severity of the disaster is high, the cost resilience-oriented model can respond to the needs of victims within the shortest time, although these needs cannot be completely met. (ii) Increasing the initial inventory level of emergency storage points and enhancing the victims’ tolerance time through social support can effectively reduce the total costs, while increasing the transportation speed can effectively reduce the response delay time. (iii) Adjusting the unit penalty cost can make the total penalty costs and transportation costs decline within a certain range, but such an adjustment has no influence on the response delay time. This paper not only proposes an integrated framework for pre- and post-disaster allocation decisions but also highlights the importance of incorporating resilience into relief item allocation in disaster contexts.

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APA

Zhang, F., Liu, Y., Yun, H., Cao, C., & Liu, X. (2025). Pre- and Post-Disaster Allocation Strategies of Relief Items in the Presence of Resilience. Systems, 13(8). https://doi.org/10.3390/systems13080704

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