## 1 Introduction
Using the Technique of Order of Preference by Similarity to the Ideal Solution (TOPSIS), which evaluates the proximity between the ideal and anti-ideal solution to achieve the smallest geometric distance to the ideal solution, that is, the one that comes closest to being the best option, in addition to the WASPAS that calculates the ratio of weights of the same alternative and the product, that is, the intersection between the criteria with respect to the same alternative, thus valuing the alternative with the highest resulting value in its relative weight ratio and the respective value of the normalized alternative. We assessed the applicability of the model in a case study to identify the most vulnerable areas and the significant risks related to human factors. Previously, the importance of each assessed factor was weighted by CRITIC. This study considers the ranking of alternatives, combining the strengths of each method, to help decision-makers allocate resources and make informed investments in emergency planning. The rising occurrence of natural disasters around the world has revealed major weaknesses in conventional evacuation planning methods. The current models of crowd movement engineering have made significant progress, but they do not include the intricate human conduct patterns that decide whether evacuations succeed or fail. The lack of consideration for psychosocial factors becomes especially critical for developing countries because their rapid urbanization and socioeconomic inequalities and insufficient infrastructure increase emergency vulnerabilities. Recent disasters including the 2010 Haiti earthquake and 2023 Chilean wildfires proved that psychological elements, together with economic differences, strongly influence how evacuations turn out. The 2015 Illapel earthquake in Chile showed that psychological paralysis and family reunification efforts caused delays in evacuation, which exceeded physical infrastructure constraints by 30 percent. Quantitative evacuation models exclude human factors from their analysis, which produces an unsafe difference between theoretical plans and actual evacuation outcomes. This study develops an innovative MCDM framework that merges human behavioral elements with standard engineering criteria to address this essential knowledge gap. The need for this work becomes more urgent because climate change projections indicate that disasters will occur more frequently in developing nations, which typically have restricted emergency response capabilities. Our CRITIC-WASPAS-TOPSIS hybrid method enables policymakers to allocate resources effectively to vulnerable groups by evaluating the multifaceted social and economic and psychological elements that influence actual evacuation results. In previous research, significant areas have been overlooked. Many existing models rely on simplistic representations of human actions. Most studies have focused on engineering solutions without adequately addressing how individuals and groups behave under stress, which can lead to suboptimal evacuation strategies. Conversely, there remains a gap in effective methodologies that synthesize insights from the social sciences, psychology, and engineering. Some studies have used an MCDM method for evacuation, but this may be insufficient as current frameworks often fail to incorporate diverse perspectives that can enhance evacuation planning and execution. This interdisciplinary approach is essential for developing realistic models that reflect human behavior during emergencies. Finally, previous studies often ignore the specific needs and behaviors of vulnerable populations during evacuations, such as the elderly, disabled individuals, or those with limited mobility. The analysis of the research gap will help improve global emergency management, contributing to the interdisciplinary analysis of human-centered catastrophic events.