Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy

Alexeeva, Tatyana; Chechurin, Leonid; Dodonov, Viktor; Honarmand, Zahra; Kuznetsov, Nikolay; Neittaanmäki, Pekka

doi:10.1080/17445760.2022.2136372

acceptedVersion

Katso/Avaa

421.0 Kb

Lataukset:

Show download details Hide download details

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 Systems

Tekijät

Dodonov, Viktor |

Päivämäärä

2023

Oppiaine

Tietotekniikka Computing, Information Technology and Mathematics Laskennallinen tiede Mathematical Information Technology Computing, Information Technology and Mathematics Computational Science

Tekijänoikeudet

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 & Francis

ISSN Hae Julkaisufoorumista

1744-5760

Lisenssi