Coupling agent-based simulation with optimization to enhance population sheltering - Systèmes Multi-Agents Coopératifs Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Coupling agent-based simulation with optimization to enhance population sheltering

Résumé

Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision-and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources.
Fichier principal
Vignette du fichier
iscram.pdf (2.76 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03633634 , version 1 (07-04-2022)

Identifiants

  • HAL Id : hal-03633634 , version 1

Citer

Ahmed Laatabi, Benoit Gaudou, Chihab Hanachi, Patricia Stolf, Sébastien Truptil. Coupling agent-based simulation with optimization to enhance population sheltering. 19th Information Systems for Crisis Response and Management Conference (ISCRAM 2022), National School of Engineers of Tarbes, France; ISCRAM Organisation, May 2022, Tarbes, France. à paraître. ⟨hal-03633634⟩
367 Consultations
86 Téléchargements

Partager

Gmail Facebook X LinkedIn More