An Optimized Evacuation Plan for an Active‐Shooter Situation Constrained by Network Capacity

ABSTRACT A total of more than 3400 public shootings have occurred in the United States between 2016 and 2022. Among these, 25.1% of them took place in an educational institution, 29.4% at the workplace, including office buildings, 19.6% in retail store locations, and 13.4% in restaurants and bars. During these critical scenarios, making the right decisions while evacuating can make the difference between life and death. However, emergency evacuation is intensely stressful, which, along with the lack of verifiable real‐time information, may lead to fatal incorrect decisions. To tackle this problem, we developed a multi‐route routing optimization algorithm that determines multiple optimal safe routes for each evacuee while accounting for available capacity along the route, thus reducing the threat of crowding and bottlenecking. Overall, our algorithm reduces the total casualties by 34.16% and 53.3%, compared to our previous routing algorithm without capacity constraints and an expert‐advised routing strategy, respectively. Further, our approach to reduce crowding resulted in an approximate 50% reduction in occupancy in key bottlenecking nodes compared to both of the other evacuation algorithms.

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Publication Details

Journal
Journal of Contingencies and Crisis Management
Published
2026-01-21
DOI
https://doi.org/10.1111/1468-5973.70113
Primary Topic
Evacuation and Crowd Dynamics
Type
article
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article

An Optimized Evacuation Plan for an Active‐Shooter Situation Constrained by Network Capacity

Aniirudh Ramesh, Subhadeep Chakraborty, Joseph Lavalle‐Rivera
Journal of Contingencies and Crisis Management
Evacuation and Crowd Dynamics
article

An Optimized Evacuation Plan for an Active‐Shooter Situation Constrained by Network Capacity

Aniirudh Ramesh, Subhadeep Chakraborty, Joseph Lavalle‐Rivera
article en

Abstract

ABSTRACT A total of more than 3400 public shootings have occurred in the United States between 2016 and 2022. Among these, 25.1% of them took place in an educational institution, 29.4% at the workplace, including office buildings, 19.6% in retail store locations, and 13.4% in restaurants and bars. During these critical scenarios, making the right decisions while evacuating can make the difference between life and death. However, emergency evacuation is intensely stressful, which, along with the lack of verifiable real‐time information, may lead to fatal incorrect decisions. To tackle this problem, we developed a multi‐route routing optimization algorithm that determines multiple optimal safe routes for each evacuee while accounting for available capacity along the route, thus reducing the threat of crowding and bottlenecking. Overall, our algorithm reduces the total casualties by 34.16% and 53.3%, compared to our previous routing algorithm without capacity constraints and an expert‐advised routing strategy, respectively. Further, our approach to reduce crowding resulted in an approximate 50% reduction in occupancy in key bottlenecking nodes compared to both of the other evacuation algorithms.

Journal of Contingencies and Crisis ManagementVol. 34(1)
Knoxville College (US), University of Tennessee at Knoxville (US)
Sustainable cities and communities
Openalex Percentile: Top 81%
Evacuation and Crowd Dynamics
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An Optimized Evacuation Plan for an Active‐Shooter Situation Constrained by Network Capacity — Aniirudh Ramesh, Subhadeep Chakraborty, et al. · Journal of Contingencies and Crisis Management (2026) | TGRS Research Map | TGRS