Shyshatsky, AndriiStasiuk, TetianaKuzmenko, Oleg2023-11-232023-11-232023Shyshatsky, A. The Development of the Solution Search Method Based on the Improved Bee Colony Algorithm / Andrii Shyshatsky, Tetiana Stasiuk, Oleg Kuzmenko // Theoretical and Applied Cybersecurity : scientific journal. – 2023. – Vol. 5, Iss. 2. – Pp. 89–96. – Bibliogr. 11 ref.https://ela.kpi.ua/handle/123456789/62414Active digitization of people's daily life leads to the use of the decision making support systems (DMSS). DMSS is actively used in data processing, forecasting the course of various processes, providing informational support for the decision making process by decision makers. However, a number of problems arise while evaluating monitoring objects, namely: a large number of destabilizing factors affecting the efficiency of the processes of information collection, processing and transmission; high dynamism of changes in the state and composition of heterogeneous monitoring objects during the conduct of hostilities (operations); high dynamism of conducting hostilities (operations); the uncertainty of the initial situation and the noise of the initial data. In this article, a method of finding solutions based on an improved bee colony algorithm was developed. The efficiency of information processing is achieved by learning the architecture of artificial neural networks; taking into account the type of uncertainty of the information to be evaluated; the use of an improved algorithm of the bee colony, the use of an unordered linguistic scale of measurements with adjustment coefficients for the degree of awareness and the degree of noise of the initial data. An approbation of the use of the proposed method was carried out on the example of assessing the state of the operational grouping of troops (forces). The method is proposed to be used in the development of software for automated systems of control of troops and weapons, namely, in the modernization of existing and development of new automated systems of control of troops and weapons. The evaluation of the effectiveness of the proposed method showed an increase in the efficiency of the evaluation at the level of 21–28% in terms of the efficiency of information processing.enbee algorithmheterogeneous intelligence objectsintelligent systemsdecision making support systemsArticlePp. 89-96https://doi.org/10.20535/tacs.2664-29132023.2.278199519.1, 514.1280000-0001-6731-6390