ANALYSIS OF EVOLUTIONARY ALGORITHMS OF GLOBAL SEARCH OPTIMIZATION

DOI: 10.31673/2786-8362.2024.029215

Abstract

The article provides a detailed analysis of evolutionary algorithms of global search engine optimization, in
particular the genetic algorithm (GA) and the modified algorithm for searching a school of fish (FSS). The
strengths and weaknesses of the selected algorithms are investigated, their efficiency and adaptability are
evaluated. The main scientific result is the development and testing of FSS modifications, which showed
increased efficiency for tasks with a large number of variables. It is recommended to use modified
algorithms in optimization tasks in various industries where complex target functions are present, in
particular in engineering, finance and logistics. The proposed system uses an evolutionary approach to adapt
and improve search algorithms, including the use of genetic algorithms to evaluate and select the most
relevant results. This allows you to take into account the user's previous experience and generate results
that better meet his needs. The introduction of evolutionary algorithms into search engines can improve the
quality of results and provide a more personalized user experience.

Keywords: abstract, evolutionary algorithm, search engines

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