Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy
Abstract
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.
Main Authors
Format
Articles
Research article
Published
2023
Series
Subjects
Publication in research information system
Publisher
Taylor & Francis
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202402211998Use this for linking
Review status
Peer reviewed
ISSN
1744-5760
DOI
https://doi.org/10.1080/17445760.2022.2136372
Language
English
Published in
International Journal of Parallel, Emergent and Distributed Systems
Citation
- 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
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