PRACTICAL AND THEORETICAL ASPECTS OF MATHEMATICAL MODELING OF THE OPTIMIZATION PROCESS OF MANAGING MULTIGROUP BEHAVIOR OF AGENTS IN DISTRIBUTED SYSTEMS BASED ON THE GWO ALGORITHM
DOI:
https://doi.org/10.20998/2079-0023.2025.02.06Keywords:
computational intelligence, optimization methods, operations research, distributed systems, grey wolf optimizer (GWO), swarm intelligence, mathematical modeling, multi-agent systems, optimal packingAbstract
This work focused on the applied aspects and features of the gray wolf pack optimizer or the GWO algorithm in the context of application in multi-agent distributed systems. In this paper presented scientific materials regarding the proposed own ideas, assumptions, and hypotheses for analyzing and further verification in the fields of computer sciences, optimization methods and solving of applied mathematical and engineering problems. The object of the research is the process of organizing distributed systems based on computational intelligence. The subject of the research is the organization of algorithmic interaction in multi-agent intelligent systems in the context of mathematical modeling of the optimization process of multi-group behavior management. The goal of the research is to investigate the key practical and theoretical applied aspects and specifics of the application of the gray wolf pack optimizer or the GWO algorithm and its modifications; to study the features of modeling the behavior of intelligent agents of a gray wolf pack under the guidance of computational intelligence. The methods used: the method of analysis and synthesis, abstraction and concretization, comparison and analogies, the method of mathematical modeling and the method of scientific and search experiment. The results obtained: 1) analyzed the solid theoretical materials in the field of applied application of the GWO algorithm; 2) analyzed the key tactical and strategical techniques of mathematical modeling of the behavior of intelligent agents; 3) formed general approaches to mathematical modeling of multi-group interaction of self-organized multi-agent formations; 4) considered and analyzed the problems of coordination and agents interaction in a multi-agent distributed system; 5) considered the applied application of multi-agent systems in problems of science, engineering, computer and robotic systems; 6) identified the main limitations of the application of the gray wolf pack algorithm (GWO). Further developed the concept of mathematical modeling of the gray wolf pack algorithm (GWO) using the example of separately selected tactical and strategic techniques for organizing a wolf pack in the form of a multi-group multi-agent distributed system. Scientific novelty: proposed a new way to solve already solved selected optimization problems (separate optimal spherical objects packing into limited container problems) that we have listed in the paper. The main idea of the paperwork is to increase the iterational speed and accuracy of the search algorithm process by using a heuristic swarm intelligence algorithm, known as the Gray Wolf pack Optimizer or the GWO index. We proposed the use of a special qualitative and numerical indicator to determine the efficiency of individual wolf pack agents by using evaluation parameters during the optimization process or in real time. Were defined new tactical and strategic methods of wolf packs organization in the process of self-organizing in a pack. Practical Significance: 1) we put forward an idea-hypothesis, for verification in subsequent works, which is based on multi-group multi-agent self-organization of a distributed system on the basis of qualitative and numerical indicators, which are planned to be calculated based on complex coordination-characteristic methods and heuristic dynamically changing data. It is proposed to verify the hypothesis about new calculated evaluation parameters of the effectiveness of wolf pack agents; 2) future research works are planned to expand the scope of application of the gray wolf pack algorithm (GWO) in combination with our other promising ideas in the field of computational intelligence for solving already known, but inefficiently solved optimization problems; 3) in the context of the process of mathematical modeling using the GWO algorithm, it is planned to pay attention to the problem of the artificiality of the principle of generation and distribution of a random variable in stochastic variables of the algorithm, the issues of which were not sufficiently covered in the works found in the references or can be modified to increase the efficiency of the algorithm in solving selected problems; 4) proposed as a new solution to use the GWO algorithm in the selected optimal spherical objects packing problems for solving them in more efficient way. Conclusions: this work considered the main practical and theoretical aspects and many-sided application of the optimization algorithm of the gray wolf pack optimizer (GWO). The applied application of this algorithm in various scientific and practical problems in the context of mathematical modeling of multigroups multiple-agents behavior was considered. The basic principles of the organization of a wolf pack were analyzed and separate strategies of coordination and hunting by a wolf pack were determined. The key characteristics and problems of the gray wolf pack optimizer algorithm (GWO) were defined and considered the ways to solve them in the most efficient way.
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