A three-stage stochastic model for emergency relief planning considering secondary disasters

In the real world, secondary disasters occur frequently after primary disasters, and their diverse and uncertain nature along with the destruction may make the emergency relief operations more challenging. A scenario-based three-stage stochastic programming model is proposed considering the correlation between primary and secondary disasters under uncertain conditions. In order to enhance the computational tractability of the model, an accelerated Benders decomposition algorithm is formulated. In addition, to tackle large-scale cases, an approximation method employing the worst-case scenario in the third stage is established to improve the computational tractability. A computational study is performed to highlight the significance of the model and the efficiency of the proposed solution strategy. The results indicate that, by considering secondary disasters, demand satisfaction can be considerably improved compared with considering only primary disasters.

Automated summary

This study proposes a scenario-based model considering the correlation between primary and secondary disasters, making emergency relief operations more challenging. An accelerated Benders decomposition algorithm and an approximation method using worst-case scenarios are formulated to enhance computational tractability. The computational study shows that considering secondary disasters can significantly improve demand satisfaction.