Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy
| dc.contributor.author | Alexeeva, Tatyana | |
| dc.contributor.author | Chechurin, Leonid | |
| dc.contributor.author | Dodonov, Viktor | |
| dc.contributor.author | Honarmand, Zahra | |
| dc.contributor.author | Kuznetsov, Nikolay | |
| dc.contributor.author | Neittaanmäki, Pekka | |
| dc.date.accessioned | 2024-02-21T09:48:04Z | |
| dc.date.available | 2024-02-21T09:48:04Z | |
| dc.date.issued | 2023 | |
| dc.identifier.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. <i>International Journal of Parallel, Emergent and Distributed Systems</i>, <i>38</i>(2), 99-109. <a href="https://doi.org/10.1080/17445760.2022.2136372" target="_blank">https://doi.org/10.1080/17445760.2022.2136372</a> | |
| dc.identifier.other | CONVID_159527976 | |
| dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/93531 | |
| dc.description.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. | en |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | eng | |
| dc.publisher | Taylor & Francis | |
| dc.relation.ispartofseries | International Journal of Parallel, Emergent and Distributed Systems | |
| dc.rights | In Copyright | |
| dc.subject.other | optimal control | |
| dc.subject.other | nonlinear dynamics | |
| dc.subject.other | economic growth | |
| dc.subject.other | balanced economy | |
| dc.subject.other | genetic algorithms | |
| dc.title | Optimal control and genetic algorithms in modeling dynamical allocation of resources for a three-sector economy | |
| dc.type | article | |
| dc.identifier.urn | URN:NBN:fi:jyu-202402211998 | |
| dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
| dc.contributor.laitos | Faculty of Information Technology | en |
| dc.contributor.oppiaine | Tietotekniikka | fi |
| dc.contributor.oppiaine | Computing, Information Technology and Mathematics | fi |
| dc.contributor.oppiaine | Laskennallinen tiede | fi |
| dc.contributor.oppiaine | Mathematical Information Technology | en |
| dc.contributor.oppiaine | Computing, Information Technology and Mathematics | en |
| dc.contributor.oppiaine | Computational Science | en |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
| dc.description.reviewstatus | peerReviewed | |
| dc.format.pagerange | 99-109 | |
| dc.relation.issn | 1744-5760 | |
| dc.relation.numberinseries | 2 | |
| dc.relation.volume | 38 | |
| dc.type.version | acceptedVersion | |
| dc.rights.copyright | © 2023 Taylor & Francis | |
| dc.rights.accesslevel | openAccess | fi |
| dc.subject.yso | talouskasvu | |
| dc.subject.yso | optimointi | |
| dc.subject.yso | geneettiset algoritmit | |
| dc.format.content | fulltext | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p6150 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p13477 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p7987 | |
| dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
| dc.relation.doi | 10.1080/17445760.2022.2136372 | |
| dc.type.okm | A1 |
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