Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy. Issue 2 (4th March 2023)
- Record Type:
- Journal Article
- Title:
- Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy. Issue 2 (4th March 2023)
- Main Title:
- Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy
- Authors:
- Alexeeva, Tatyana
Chechurin, Leonid
Dodonov, Viktor
Honarmand, Zahra
Kuznetsov, Nikolay
Neittaanmäki, Pekka - Abstract:
- 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. GRAPHICAL ABSTRACT: UF0001
- Is Part Of:
- International journal of parallel, emergent and distributed systems. Volume 38:Issue 2(2023)
- Journal:
- International journal of parallel, emergent and distributed systems
- Issue:
- Volume 38:Issue 2(2023)
- Issue Display:
- Volume 38, Issue 2 (2023)
- Year:
- 2023
- Volume:
- 38
- Issue:
- 2
- Issue Sort Value:
- 2023-0038-0002-0000
- Page Start:
- 99
- Page End:
- 109
- Publication Date:
- 2023-03-04
- Subjects:
- Optimal control -- nonlinear dynamics -- economic growth -- balanced economy -- genetic algorithms
Parallel computers -- Periodicals
Electronic data processing -- Distributed processing -- Periodicals
Computer algorithms -- Periodicals
004.35 - Journal URLs:
- http://www.tandfonline.com/toc/gpaa20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/17445760.2022.2136372 ↗
- Languages:
- English
- ISSNs:
- 1744-5760
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.441300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 26157.xml