Track: Decision Sciences

Abstract

Disaster management is vital, and it faces a variety of problems. It is a form of governance that aims to plan, direct, support, coordinate, and effectively implement the activities that should be done before and after the event to prevent disasters and reduce their damage. Disaster management has a multi-faceted, multi-actor, multi-disciplinary, dynamic, comprehensive, and complex structure. In this context, the study aims to propose an action plan evaluation framework for disaster management and to prioritize these action plans with Hesitant Fuzzy Linguistic (HFL) Simple Additive Weighting (SAW)-COmplex PRoportional ASsessment (COPRAS) methods. Considering the complex and uncertain nature of this multi-criteria decision-making (MCDM) problem, Hesitant Fuzzy Linguistic Terms Sets (HFLTS) is employed. This technique is applied to provide flexibility to experts using comparative linguistic expressions and obtain an evaluation environment closer to human thinking. The integrated HFL SAW-COPRAS methodology is practical, flexible, reliable, robust, adaptable to different fuzzy environments, and maximizing the benefit while minimizing the cost of alternatives. The evaluation factors and action plans are determined based on a literature review and experts' consulting. HFL SAW method is applied to find the weights of evaluation factors, and action plans are prioritized with the HFL COPRAS method. An illustrative application of disaster management is provided to illustrate the effectiveness of the proposed methodology. Finally, the results of this paper showed that the most appropriate factor is“Risk Planning and Control," and the first ranked action plan is "Planning & Organization"