Title: Stability-based model for evacuation system using agent-based social simulation and Monte Carlo method
Authors: Makhlouf Naili; Mustapha Bourahla; Mohamed Naili
Addresses: Department of Computer Science, University of Biskra, 07000 Biskra, Algeria ' Department of Computer Science, University of M'Sila, 28000 M'Sila, Algeria ' Department of Computer Science, University of Bordj Bou Arreridj, 34030 Bordj Bou Arreridj, Algeria
Abstract: The agent-based modelling is used for modelling many complex dynamic systems, especially those including autonomous individuals such as human beings' societies, animals' societies, robots, insects' societies, etc. Evacuation systems such as those needed for supermarket buildings are considered as complex dynamic systems. In these systems, we have to deal with the problem of rescuing a high number of people of different ages, sex, physical characteristics, etc. Furthermore, this process mostly runs in buildings with different constraints like locations of the rows of shelves, exit gates, etc. On one hand, in order to deal with disasters such as fire propagation, studying this kind of system using a dynamic model has a great importance in order to avoid the maximum of casualties. On the other hand, the model that represents this kind of system must take into account several factors such as time, the building's characteristics and people's characteristics. In this study, an agent-based model has been designed to visualise the dynamic system behaviour via these internal entities that often interact. Additionally, we use some dynamic data mining methods such as Monte Carlo method to calculate the stable characteristics of this model via probabilistic approach.
Keywords: agent-based modelling; ABM; dynamic data mining; dynamic models; evacuation building system; modelling; Monte Carlo simulation; simulation; stability; steady state.
International Journal of Simulation and Process Modelling, 2019 Vol.14 No.1, pp.1 - 16
Received: 21 Oct 2017
Accepted: 09 Apr 2018
Published online: 01 Feb 2019 *