A framework for evaluation of resilience of disaster rescue networks

Abstract

Disasters by their very nature are unpredictable so being prepared to react in short time and with high efficiency is vital. The adoption of the collaborative networks paradigm in disaster management can lead to a new generation of rescue teams so called Disaster Rescue Network (DRN). During the first hours after a disaster, and before external help can arrive, it is the DRN implanted in the incident area that can perform the first rescue tasks. But the DRN is itself affected by the disaster and often gets its operational level drastically reduced. The main objective of this work is to propose an evaluation model, through employing experts’ knowledge, for measuring a resilience index in DRNs. In this paper, a Fuzzy Inference System is used to achieve the mentioned objective. This will help in evaluating the resilience of DRNs and provide the opportunity to simulate policies to improve that resilience.