The Use of Evolutionary Algorithms for Optimization in the Modern Entrepreneurial Economy: Interdisciplinary Perspective


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.


evolutionary algorithms; genetic algorithms; computational techniques; optimization techniques; entrepreneurial economy

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Published : 2019-12-27

Sieja, M., & Wach, K. (2019). The Use of Evolutionary Algorithms for Optimization in the Modern Entrepreneurial Economy: Interdisciplinary Perspective. Entrepreneurial Business and Economics Review, 7(4), 117-130.

Marek Sieja
Cracow University of Technology  Poland
Krzysztof Wach 
University of Social Sciences in Łódź  Poland

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