The use of evolutionary algorithms for optimization in the modern entrepreneurial economy: interdisciplinary perspective
Authors:
- Marek Sieja,
- Krzysztof Wach
Abstract
Objective: The objective of the article is to present the concept of evolutionary algorithms and indicates the possibility of their implementation for the needs of the economy, especially the entrepreneurial economy. Research Design & Methods: This conceptual article relies on literature review and desk research. The article elaborates on available literature via a systematic literature review methodology. Findings: The article elaborates on the idea of action and typology of evolutionary algorithms as the broadly applied search and optimisation technique based on Darwin’s theory of evolution and modern natural genetics. The article focuses on the examples of evolutionary algorithms application in economics and management. Implications & Recommendations: The current state of applications of evolutionary algorithms for the needs of the economy and business confirms that we still await an implementation breakthrough. The growing interest in evolutionary algorithms in connection with the dynamic development of information technologies may lead to the use of evolutionary algorithms in hybrid systems, which in turn will contribute to significant progress in optimization theory. Contribution & Value Added: The article structures scientific knowledge on the application of evolutionary algorithms in business and economy. The promotion of the application of evolutionary algorithms in economics, finance, and management is mainly limited to journals in operational research, decision-making process, or financial engineering, whereas this article includes entrepreneurship.
- Record ID
- CUT75d2a29cafd14cb9b440f2b77e47c59a
- Publication categories
- ;
- Author
- Journal series
- Entrepreneurial Business and Economics Review, ISSN 2353-883X, e-ISSN 2353-8821
- Issue year
- 2019
- Vol
- 7
- No
- 4
- Pages
- 117-130
- Other elements of collation
- rys.; tab.; Bibliografia (na s.) - 127-129; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 7, No. 4
- Keywords in English
- evolutionary algorithms, genetic algorithms, computational techniques, optimization techniques, entrepreneurial economy
- DOI
- DOI:10.15678/EBER.2019.070407 Opening in a new tab
- URL
- https://eber.uek.krakow.pl/index.php/eber/article/view/617 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 100
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT75d2a29cafd14cb9b440f2b77e47c59a/
- URN
urn:pkr-prod:CUT75d2a29cafd14cb9b440f2b77e47c59a
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.