TY - GEN
T1 - A Graph-Based Adaptive Routing Optimization Algorithm for Emergency Evacuations
AU - Behrooz, Hojat
AU - Ilbeigi, Mohammad
N1 - Publisher Copyright:
© ASCE.
PY - 2025
Y1 - 2025
N2 - Emergency evacuation routing is a critical component of disaster management, ensuring individuals’ safe and timely relocation from hazardous areas to safe zones. Traditional evacuation planning relies on static, preplanned strategies that often lack adaptability to evolving disaster scenarios. This study presents a novel dynamic graph-based routing method that optimizes evacuation efficiency by adjusting road segment directions in real-time. The proposed algorithm iteratively distributes traffic flow across the network using a depth first search (DFS)based approach, dynamically reconfiguring road topology to maximize the flow of vehicles. Implemented in the road network of Hoboken, New Jersey, the method demonstrated a 74% improvement in evacuation efficiency compared to benchmark methods that lack adaptive road reconfiguration. The findings highlight the transformative potential of this approach in supporting real-time decision-making during emergencies, offering a robust tool for adaptive evacuation planning.
AB - Emergency evacuation routing is a critical component of disaster management, ensuring individuals’ safe and timely relocation from hazardous areas to safe zones. Traditional evacuation planning relies on static, preplanned strategies that often lack adaptability to evolving disaster scenarios. This study presents a novel dynamic graph-based routing method that optimizes evacuation efficiency by adjusting road segment directions in real-time. The proposed algorithm iteratively distributes traffic flow across the network using a depth first search (DFS)based approach, dynamically reconfiguring road topology to maximize the flow of vehicles. Implemented in the road network of Hoboken, New Jersey, the method demonstrated a 74% improvement in evacuation efficiency compared to benchmark methods that lack adaptive road reconfiguration. The findings highlight the transformative potential of this approach in supporting real-time decision-making during emergencies, offering a robust tool for adaptive evacuation planning.
UR - https://www.scopus.com/pages/publications/105030953172
UR - https://www.scopus.com/pages/publications/105030953172#tab=citedBy
U2 - 10.1061/9780784486443.014
DO - 10.1061/9780784486443.014
M3 - Conference contribution
AN - SCOPUS:105030953172
T3 - Computing in Civil Engineering 2025: Resilient, Robotic, and Educational Systems - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2025
SP - 115
EP - 123
BT - Computing in Civil Engineering 2025
A2 - Jafari, Amirhosein
A2 - Zhu, Yimin
T2 - ASCE International Conference on Computing in Civil Engineering, i3CE 2025
Y2 - 11 May 2025 through 14 May 2025
ER -