MAX-MIN Ant System; Network Disruption Analysis; River Floods; Agent-based Modelling; Travel Demand
Abstract :
[en] This paper presents a model for understanding short-term travelers’ behavior in the context of river floods. In several cities, river floods are considerably affecting urban transportation systems. In this regard, decision makers need comprehensive models to define efficient risk management strategies. The dynamic nature of this problem requires an algorithm able to deal with traffic redirecting during the micro-simulation process. Furthermore, a transportation network contains a significant number of links and nodes which lead to large computation times. In this regard, an Ant Colony Optimization (ACO) algorithm is proposed to solve such combinatorial problems. In a basic ACO, some ants/agents might push the algorithm to converge toward non-optimal solutions. In this context, a MAX-MIN Ant System (AS) approach is included in the algorithm to stimulate the best solutions. In addition, the discrete choice model is adapted to allow more behavioral reactions regarding simulated river floods.
Research center :
Lepur : Centre de Recherche sur la Ville, le Territoire et le Milieu rural - ULiège LEMA : Local Environment Management & Analysis
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Saadi, Ismaïl ; Université de Liège > Département ArGEnCo > Transports et mobilité
Teller, Jacques ; Université de Liège > Département ArGEnCo > Urbanisme et aménagement du territoire
Limbourg, Sabine ; Université de Liège > HEC-Ecole de gestion : UER > UER Opérations : Logistique
Cools, Mario ; Université de Liège > Département ArGEnCo > Transports et mobilité
Language :
English
Title :
Modelling Agents’ Behavior in the Context of River Floods: An Ant Colony based Approach
Publication date :
September 2015
Event name :
11th International Conference of Eastern Asia Society for Transportation Studies (EASTS 2015)
Event place :
Cebu City, Philippines
Event date :
September 11-14, 2015
Audience :
International
References of the abstract :
This paper presents a model for understanding short-term travelers’ behavior in the context of river floods. In several cities, river floods are considerably affecting urban transportation systems. In this regard, decision makers need comprehensive models to define efficient risk management strategies. The dynamic nature of this problem requires an algorithm able to deal with traffic redirecting during the micro-simulation process. Furthermore, a transportation network contains a significant number of links and nodes which lead to large computation times. In this regard, an Ant Colony Optimization (ACO) algorithm is proposed to solve such combinatorial problems. In a basic ACO, some ants/agents might push the algorithm to converge toward non-optimal solutions. In this context, a MAX-MIN Ant System (AS) approach is included in the algorithm to stimulate the best solutions. In addition, the discrete choice model is adapted to allow more behavioral reactions regarding simulated river floods.
