Mathematical Programming for Optimal Evacuation in Industrial Facilities

This paper presents an optimization framework for determining safe and efficient evacuation paths in complex industrial facilities. The proposed approach models the evacuation process through a timed flow network that captures both the structural characteristics of the layout and the temporal evolution of emergency conditions. The formulation accommodates real-time updates, enabling dynamic re-routing when certain areas or connections become inaccessible. Computational experiments on large-scale instances demonstrate the scalability of the model and its ability to provide complete evacuation plans under increasing demand. The results confirm predictable relationships between population size, time horizon, and evacuation completion, supporting its use as a decision support tool for both strategic planning and operational response.

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Publication Details

Journal
Mathematics
Published
2026-02-11
DOI
https://doi.org/10.3390/math14040632
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
0.00
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article

Mathematical Programming for Optimal Evacuation in Industrial Facilities

Carmine Cerrone, Anna Sciomachen
Mathematics
Evacuation and Crowd Dynamics
article

Mathematical Programming for Optimal Evacuation in Industrial Facilities

Carmine Cerrone, Anna Sciomachen
article en

Abstract

This paper presents an optimization framework for determining safe and efficient evacuation paths in complex industrial facilities. The proposed approach models the evacuation process through a timed flow network that captures both the structural characteristics of the layout and the temporal evolution of emergency conditions. The formulation accommodates real-time updates, enabling dynamic re-routing when certain areas or connections become inaccessible. Computational experiments on large-scale instances demonstrate the scalability of the model and its ability to provide complete evacuation plans under increasing demand. The results confirm predictable relationships between population size, time horizon, and evacuation completion, supporting its use as a decision support tool for both strategic planning and operational response.

MathematicsVol. 14(4)
University of Genoa (IT)
Sustainable cities and communities
Openalex Percentile: Top 58%
Evacuation and Crowd Dynamics
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