Statement the Problem of Simulation of Decision-Making Processes in Complex Organizational-Technical Systems

The problem that is solved in the research is to increase the efficiency of decision making in management tasks while ensuring the given reliability, regardless of the hierarchical nature of the object. The object of the research is decision making support system. The subject of the research is the decision making process in management tasks using an improved wolf flock algorithm. The hypothesis of the research is to increase the efficiency of decision making with a given assessment reliability. In the course of the research, an improved optimization method based on an improved wolf flock algorithm was proposed. In the course of the conducted research, the general provisions of the theory of artificial intelligence were used to solve the problem of analyzing the objects state and subsequent parametric management in intelligent decision making support systems. The essence of the improvement lies in the use of the following procedures, which improve basic procedures of the wolf flock algorithm, namely search and chase: – taking into account the type of uncertainty of the initial data while constructing the wolf flock path metric; – searching for a solution in several directions using individuals from the wolf flock; – initial presentation of individuals from the wolf flock; – an improved procedure for adapting a flock of wolves; – taking into account the available computing resources while choosing the number of leaders in a flock of wolves. An example of the use of the proposed method is presented on the example of assessing the state of the operational situation of a group of troops (forces). The specified example showed an increase in the efficiency of data processing at the level of 23–30 % due to the use of additional improved procedures

“…-the possibility of finding a solution in several directions in comparison with works [9][10][11][12][13][14][15][17][18][19][20][21];…”

Section: Discussion Of the Results Of The Development Of The Optimiza...mentioning

confidence: 99%

Section: Analysis Of Literary Data and Formulation Of The Problemmentioning

confidence: 99%

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Improvement of the optimization method based on the wolf flock algorithm

Trotsko

Protas

Odarushchenko

et al. 2023

“…The work [21] presents a cognitive approach to simulation modeling of complex systems. The advantages of the specified approach, which allows describing the hierarchical components of the system, are shown.…”

Section: Improved Search Procedures For the Parametric Optimization M...mentioning

confidence: 99%

Improvement of the optimization method based on the cat pack algorithm

Koval

Nechyporuk

Shyshatskyi

et al. 2023

The problem that is being solved in the research is to increase the efficiency of decision-making in management tasks while ensuring the given reliability, regardless of the hierarchical nature of the object. The object of research is the decision-making support systems. The subject of the research is the decision-making process in management tasks using an improved cat flock algorithm. The research hypothesis is the possibility of increasing the efficiency of decision-making with a given assessment reliability. In the course of the research, an improved method of parametric optimization based on the improved algorithm of the cat flock was proposed. In the course of the research, the general provisions of the theory of artificial intelligence were used to solve the problem of analyzing the state of objects and subsequent parametric management in intelligent decision-making support systems. The essence of the method improvement lies in the use of the following procedures, which improve basic procedures of the cat flock algorithm, namely, search and chase: – training of individuals of a cat flock with the help of evolving artificial neural networks; – taking into account the type of uncertainty of the initial data while constructing the metric of the path of the cat flock, which reduces the time of searching for the optimal solution; – searching for a solution in several directions using individuals from the cat flock, which reduces the time of searching for the optimal solution; – initial display of individuals from the cat flock not randomly; – additional consideration of the chase parameter, which limits the chase area, which allows to take into account the priority of the search; – the ability to determine the need to involve additional network hardware resources. An example of the use of the proposed method is presented on the example of assessing the state of the operational situation of a group of troops (forces). The specified example showed a 17–23 % increase in the efficiency of data processing due to the use of additional improved procedures

“…The work [21] presents a cognitive approach to the simulation of complex systems. The advantages of the specified approach, which allows you to describe the hierarchical components of the system, are shown.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of a method for the search of solutions in the sphere of national security using bio-inspired algorithms

Koval,

Shyshatskyi,

Ransevych

et al. 2023

The object of research are decision support systems. The subject of research is the decision-making process in management problems using bio-inspired algorithms. A method for the search of solutions in the field of national security using bio-inspired algorithms is proposed. The proposed method is based on a combination of an artificial bat algorithm and evolving artificial neural networks. The method has the following sequence of actions: ‒ input of initial data; ‒ processing of initial data taking into account the degree of uncertainty; ‒ numbering of bat agents (BA); ‒ placement of bat agents taking into account the degree of uncertainty about the state of the analysis object in the search space; ‒ setting the initial BA speed and the echolocation frequency of each BA; ‒ starting a local search; ‒ launching a global search; ‒ training knowledge bases of bat agents. The originality of the proposed method consists in the arrangement of bat agents taking into account the uncertainty of initial data, improved global and local search procedures taking into account the noise degree of data about the state of the analysis object. Another feature of the proposed method is the use of an improved procedure for training bat agents. The training procedure consists in learning the synaptic weights of an artificial neural network, the type and parameters of the membership function, the architecture of individual elements and the architecture of the artificial neural network as a whole. The method makes it possible to increase the efficiency of data processing at the level of 13–21 % due to the use of additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interests of solving national security problems