Multi-expert disaster risk management & response capabilities assessment using interval-valued intuitionistic fuzzy sets

Abstract

This study focuses on the evaluation of disaster risk management and response (DRMR) processes and capabilities using a multi-expert multi-criteria decision making (MCDM) framework. The proposed framework considers four sets of evaluation and performance criteria: risk knowledge and organization, risk reduction, disaster response management, and disaster response support; and 22 sub-criteria such as regulating risk management, financial management, energy, and public safety. To contend with random perception and utility, lack of information and subjectivity in the human (expert) judgment processes that could be present in expert-based models, the authors propose an interval-valued intuitionistic fuzzy sets (IVIFSs) approach. IVIFSs can handle high levels of uncertainty and define appropriate membership functions. Specifically, the proposed approach incorporates score judgement and possibility degree matrices, and estimates the local and global weights for each assessment criteria. And finally, evaluates the overall performances of the alternatives using intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The authors implemented the framework to the Atlantico State of Colombia, and assessed the disaster risk management and response processes for each for the State's 23 municipalities. The authors discuss sensitivity analysis that illustrates the robustness of the results.