Development of a solution search method using an improved locust swarm algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.287316

Keywords:

swarm intelligence, decision support systems, hierarchical systems, locust swarm algorithm

Abstract

The object of the research is decision support systems. The subject of the research is the decision-making process in management problems using the locust swarm algorithm and evolving artificial neural networks.

A solution search method using an improved locust swarm algorithm is proposed. The research is based on the locust swarm algorithm for finding a solution regarding the state of an object. For training locust agents (LA), evolving artificial neural networks are used. The method has the following sequence of steps:

– input of initial data;

– processing of initial data taking into account the degree of uncertainty;

– initial setting of LA in the search area;

– determination of the initial speed of the LA movement;

– a search vector is generated taking into account the degree of uncertainty;

– calculation of the change in the value of the LA fitness function;

– training of LA knowledge bases.

The originality of the proposed method lies in the arrangement of LA taking into account the uncertainty of the initial data, improved procedures of global and local search taking into account the degree of noise of data about the state of the analysis object. Also, the originality of the research is avoiding the concentration of LA on the current best positions, reducing the probability of premature convergence of the algorithm and maintaining a balance between the convergence rate of the algorithm and diversification. The peculiarity of the proposed method is the use of an improved procedure for LA training. The training procedure consists in learning the parameters and architecture of individual elements and the architecture of the artificial neural network as a whole

Author Biographies

Vitalii Tyurin, The National Defence University of Ukraine

PhD, Associate Professor, Chief Researcher

The Scientific and Methodological Center of Scientific, Scientific and Technical Activities Organization

Robert Bieliakov, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

PhD, Assosiate Professor

Elena Odarushchenko, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Volodymyr Yashchenok, Ivan Kozhedub Kharkiv National Air Force University

PhD, Associate Professor, Head of Department

Department of Design and Durability of Aircraft and Engines

Olena Shaposhnikova, Kharkiv National Automobile and Highway University

PhD, Associate Professor

Department of Computer Systems

Anna Lyashenko, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Researcher

Scientific Center

Oleksandr Stanovskyi, Odessа Polytechnic National University

Doctor of Technical Sciences, Professor

Department of Integrated Management Technologies

Borys Melnyk, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Head

Scientific-Research Department

Sviatoslav Sus, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Researcher

Scientific-Research Department

Mykola Dvorskyi, Scientific-Research Institute of Military Intelligence

Researcher

Research Department

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Development of a solution search method using an improved locust swarm algorithm

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Published

2023-10-31

How to Cite

Tyurin, V., Bieliakov, R., Odarushchenko, E., Yashchenok, V., Shaposhnikova, O., Lyashenko, A., Stanovskyi, O., Melnyk, B., Sus, S., & Dvorskyi, M. (2023). Development of a solution search method using an improved locust swarm algorithm. Eastern-European Journal of Enterprise Technologies, 5(4 (125), 25–33. https://doi.org/10.15587/1729-4061.2023.287316

Issue

Vol. 5 No. 4 (125) (2023): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2023 Vitalii Tyurin, Robert Bieliakov, Elena Odarushchenko, Volodymyr Yashchenok, Olena Shaposhnikova, Anna Lyashenko, Oleksandr Stanovskyi, Borys Melnyk, Sviatoslav Sus, Mykola Dvorskyi

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