Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy
Alexeeva, T., Chechurin, L., Dodonov, V., Honarmand, Z., Kuznetsov, N., & Neittaanmäki, P. (2023). Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy. International Journal of Parallel, Emergent and Distributed Systems, 38(2), 99-109. https://doi.org/10.1080/17445760.2022.2136372
Julkaistu sarjassa
International Journal of Parallel, Emergent and Distributed SystemsTekijät
Päivämäärä
2023Oppiaine
TietotekniikkaComputing, Information Technology and MathematicsLaskennallinen tiedeMathematical Information TechnologyComputing, Information Technology and MathematicsComputational ScienceTekijänoikeudet
© 2023 Taylor & Francis
The task of looking for the optimal allocation of resources in an economy is fraught with a number of severe restrictions. This is manifested in the complexity of the technical implementation of the solution even in the case of a low dimension of the problem. In this paper, we consider two approaches, analytical and numerical, for deriving the dynamical optimal allocation of resources in a three-sector economy and show that the use of modern artificial intelligence (AI) technologies such as genetic algorithms (GA), can be useful for expanding the range of effective tools and new contributions to this problem.
Julkaisija
Taylor & FrancisISSN Hae Julkaisufoorumista
1744-5760Asiasanat
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https://converis.jyu.fi/converis/portal/detail/Publication/159527976
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