@ARTICLE{26583204_580904904_2022, 
	author = {Valery Makarov and Albert Bakhtizin and Gayane Beklaryan and Andranik Akopov and Nikita Strelkovskii}, 
	keywords = {, agent-based modeling, migration and demographic processes, population dynamics, large-scale modeling, parallel computing on GPU, supercomputer modelingdecision support},
	title = {<p class="text">Simulation of migration and demographic processes using FLAME&nbsp;GPU</p>},
	journal = {},
	year = {2022},
	number = {1 Vol 16},
	pages = {7-21},
	url = {https://bijournal.hse.ru/en/2022--1 Vol 16/580904904.html},
	publisher = {},
	abstract = {&nbsp; &nbsp; &nbsp; This article presents an approach to modeling migration and demographic processes using a framework designed for large-scale agent-based modeling - FLAME GPU. This approach is based on the previously developed simulation model of interaction between two communities: migrants and natives that is implemented in the AnyLogic simulation software. The model has had a low dimensionality of the discrete space representing the operating environment of the agent populations and a deterministic decision-making system of each agent. At the same time, the presence of multiple interactions between agents and transitions between their states determines a high computational complexity of such a model. The use of FLAME GPU makes it possible to conduct extensive simulation experiments with the model, mainly due to the parallelization of computational processes at the level of each agent, as well as the implementation of the mechanism of multiple computations using Monte Carlo techniques. The developed framework is used to study the impact of the most important parameters of the model (e.g., rate of migration, governmental expenditures on integration, frequency of creation of new workplaces, etc.) on the key outputs of the modeled socio-economic system (in particular, population size, share of migrants, number of assimilated migrants, GDP growth rate, etc.). The proposed approach can be used to develop decision-making systems for planning the hiring of new employees based on the forecast dynamics of migration and demographic processes.},
	annote = {&nbsp; &nbsp; &nbsp; This article presents an approach to modeling migration and demographic processes using a framework designed for large-scale agent-based modeling - FLAME GPU. This approach is based on the previously developed simulation model of interaction between two communities: migrants and natives that is implemented in the AnyLogic simulation software. The model has had a low dimensionality of the discrete space representing the operating environment of the agent populations and a deterministic decision-making system of each agent. At the same time, the presence of multiple interactions between agents and transitions between their states determines a high computational complexity of such a model. The use of FLAME GPU makes it possible to conduct extensive simulation experiments with the model, mainly due to the parallelization of computational processes at the level of each agent, as well as the implementation of the mechanism of multiple computations using Monte Carlo techniques. The developed framework is used to study the impact of the most important parameters of the model (e.g., rate of migration, governmental expenditures on integration, frequency of creation of new workplaces, etc.) on the key outputs of the modeled socio-economic system (in particular, population size, share of migrants, number of assimilated migrants, GDP growth rate, etc.). The proposed approach can be used to develop decision-making systems for planning the hiring of new employees based on the forecast dynamics of migration and demographic processes.}
}