[en] Synthetic populations are tools widely spread in the agent-based community for representing a baseline population of interest whose dynamics and evolution will be simulated and studied. The dynamic evolution of the synthetic population has been typically performed using a discrete and fixed time step. A continuous approach based on the Gillespie algorithm is proposed in this research. Preliminary experiments illustrate the potential of the new method before future work are discussed.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Barthélemy, Johan ; University of Wollongong, Wollongong, Australia
Dumont, Morgane ; Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Quantitative Models and Methods in Management ; University of Namur, Namur, Belgium
Carletti, Timoteo ; University of Namur, Namur, Belgium
Language :
English
Title :
Towards the Evolution of Synthetic Population in Continuous Time
Publication date :
2021
Event name :
15th Social Simulation Conference
Event place :
Mainz, Deu
Event date :
23-09-2019 => 27-09-2019
Audience :
International
Main work title :
Advances in Social Simulation - Proceedings of the 15th Social Simulation Conference, 2019
Fig. 19.5 Number of births per month assuming a constant uniform probability distribution over the year (left panel) and a non-uniform probability distribution (right panel) Acknowledgements The authors wish to thank their respective institution for their continuous support. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research.
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F. Gargulio, S. Ternes, S. Huet, G. Deffuant, An iterative approach for generating statistically realistic populations of households. PLoS ONE 5(1), e8828 (2010)
J. Barthélemy, P.L. Toint, Synthetic population generation without a sample. Transp. Sci. 47(2), 266–279 (2013)
N. Huynh, J. Barthelemy, P. Perez, A heuristic combinatorial optimisation approach to synthe-sising a population for agent based modelling purposes. J. Artif. Soc. Soc. Simul. 19(4), 11 (2016)
P. Ye, X. Hu, Y. Yuan, F.Y. Wang, Population synthesis based on joint distribution inference without disaggregate samples. J. Artif. Soc. Soc. Simul. 20(4), 1–16 (2017)
M. Lenormand, G. Deffuant, Generating a synthetic population of individuals in households: sample-free vs sample-based methods. arXiv preprint arXiv:1208.6403 (2012)
R. Lovelace, M. Dumont, Spatial Microsimulation with R. CRC Press, (2016) doi:https://doi. org/10.1201/b20666
E.J. Miller, P.A. Salvini, The integrated land use, transportation, environment (ILUTE) microsimulation modelling system: description and current status. Travel behaviour research: The leading edge, 711–724 (2001)
E. Cornelis, J. Barthelemy, X. Pauly, F. Walle, Modélisation de la mobilité résidentielle en vue d’une micro-simulation des évolutions de population. Les Cahiers Scientifiques Du Transport 62, 65–84 (2012)
Barthélemy, J.: A parallelized micro-simulation platform for population and mobility behaviour-Application to Belgium. Ph.D. thesis, University of Namur (2014)
M. Dumont, T. Carletti, E. Cornélis, Vieillissement et entraide: Quelles méthodes pour décrire et mesurer les enjeux? Univer’Cité 6, 55 (2017)
N. Huynh, P. Perez, M. Berryman, J. Barthélemy, Simulating transport and land use interde-pendencies for strategic urban planning-An agent based modelling approach. Systems, 3(4), 177–210 (2015). doi:https://doi.org/10.3390/systems3040177
M. Dumont, J. Barthelemy, N. Huynh, T. Carletti, Towards the right ordering of the sequence of models for the evolution of a population using agent-based simulation. J. Artif. Soc. Soc. Simul. 21(4), 3 (2018)
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