Development of a method of increasing the efficiency of decision-making in organizational and technical systems

Abstract

The object of the study is organizational and technical systems. The subject of the study is the decision-making process in the problems of management of organizational and technical systems. A method of increasing the efficiency of decision-making in organizational and technical systems using artificial intelligence is proposed. The research is based on the giant armadillo swarm algorithm to find a solution regarding the state of organizational and technical systems. Giant armadillo agents (GAA) are trained using evolving artificial neural networks, and an advanced genetic algorithm is used to select the best GAA. The method has the following sequence of actions: – input of initial data; – setting GAA on the search plane; – numbering GAA in the swarm; – determining the initial velocity of GAA; – preliminary evaluation of the GAA search area; – classification of food sources for GAA; – sorting the best GAA individuals; – attack on termite mounds by GAA; – digging termite mounds by GAA; – updating GAA positions; – checking for the presence of a GAA predator; – escape and fight against GAA predators; – checking the stop criterion; – training GAA knowledge bases; – determining the amount of necessary computing resources of the intelligent decision support system. The originality of the proposed method lies in setting GAA taking into account the uncertainty of the initial data, advanced procedures of global and local search taking into account the noise degree of data on the state of organizational and technical systems. The method makes it possible to increase the efficiency of data processing at the level of 14–19 % using additional advanced procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes