A systematic review of methodologies for human behavior modelling and routing optimization in large-scale evacuation planning

Frequent and escalating natural disasters pose an increasing threat to society and the environment. Effective disaster management strategies are crucial to mitigate their impact. This paper reviews recent methodologies for large-scale evacuation planning, a key element in risk reduction. A systematic analysis of 100 articles and conference proceedings in evacuation planning, focusing on human factors/behavior modeling and evacuation routing optimization, reveals that Agent-Based Simulation (ABS) is commonly used to predict human factors/behaviors. Heuristics/metaheuristics and traffic assignment techniques dominate evacuation routing planning, often aiming to identify the shortest evacuation path. While evacuation decisions and route choice are extensively studied, optimization approaches frequently lack integration with human factors/behavior modeling. This review underscores the need for further research to enhance evacuation planning by integrating human factors/behavior and optimization methodologies for increased effectiveness and efficiency

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019