## 1 Introduction  
The growing world population will lead to greater urban settlement and is projected to reach 9.7 billion people by 2050 [1]. However, there has also been a significant increase in climatic and seismological events that pose direct risks to the sustainability and safety of cities. In emergency situations, evacuation actions are tested, and safety measures can be impaired by mass reactions, which generally involve the movement of people with little time to decide. In these cases, the decision to move taken by each individual has to be foreseen, premeditated, and trained in advance. This is important when decision-makers design evacuation plans based on previous experiences and future scenarios with an increased number and intensity of climatic and seismic events. It is also essential as a modeling problem because of the need to achieve adequate adjustments in accuracy and computational time that are appropriate for application. Pre-emergency evacuation plans lack an interdisciplinary assessment of human factors, and regardless of the type of disaster, there are priority areas that are more critical to deal with than others. Decision-makers must design appropriate plans to minimize the risk of human loss. Indeed, the problem involves people who will experience catastrophic events and who must react to emergencies in extreme situations, whether in response to a prior call to evacuate or during the event itself, such as hurricanes, storms, volcanic eruptions, earthquakes, tsunamis, floods, and even terrorist attacks. Given the diversity of possible events, their occurrence can geographically affect different human settlements, particularly in urban areas. Establishing coordination among many people in high-pressure evacuation situations or imminent survival threats remains a significant challenge. Current mathematical models can only approximate solutions, studying access points prescriptively or predictively in the dynamic evacuation setting. These models must consider the complex interactions between people, such as avoiding collisions and congestion, and the diverse behaviors and group dynamics that arise during a crisis. Evacuation plans estimate times and protocols according to the subjective experience of groups of experts or based on simulated studies [2,3], maintaining uncertainty in the possible outcomes of the evacuation plans. Existing studies on crowd management and crowd behavior focus on the simulation of scenarios and cases to assess the movement of people with different patterns of behavior using a model that appropriately emulates crowd behavior [4, 5, 6, 7] in evacuation situations prior to an imminent risk condition [8], as well as in evacuation situations where high-density groups behave differently according to the degree of interaction and concentration [9,10]. Evacuation processes are divided into pre- and post-evacuation, and the latter includes the evacuation situation itself [9, 11]. Refs. [12,13] highlighted the importance of interdisciplinarity and behavior modification in evacuation management. Previous studies used MCDM to evaluate evacuation in close spaces; for example, in [14] a methodology was used to identify risk factors in the process of human evacuation from passenger ships or to allocate facilities strategically, such as [15] presenting a comprehensive framework to guide site selection for post-earthquake emergency medical service facilities, or based on simulation and metaheuristic optimization to select the best-satisfying evacuation scenario with an MCDM method [16]. However, no studies have considered human factors in decision-making.