INTEGRATION OF ARTIFICIAL INTELLIGENCE AND OPERATIONS RESEARCH METHODS TO IMPROVE DECISION EFFICIENCY

Abstract

The article explores the relevance of integrating artificial intelligence (AI) methods and classical operations research (OR) methods to improve decision-making efficiency in complex dynamic systems. Modern organizations face exponential growth in data volumes, high uncertainty, and rapid changes in their operating environment, which requires new approaches to management and optimization. While classical operations research methods such as linear programming, game theory, queuing modeling, and heuristic algorithms remain fundamental analytical tools, their effectiveness may be limited in the face of big data and nonlinear dependencies.

The proposed study analyses the possibilities of combining artificial intelligence, in particular machine learning, deep neural networks, and evolutionary algorithms, with traditional optimization methods. Specific examples of the application of these approaches in such areas as logistics, manufacturing, finance and inventory management are considered. It is shown that the use of artificial intelligence to predict model parameters, optimize large systems and analyze complex scenarios helps to improve the accuracy of forecasts, adaptability to changes and the overall efficiency of management decisions.

The key challenges associated with the integration of artificial intelligence and operations research are discussed separately, including the computational complexity of algorithms, the need for high-quality and representative data sets, and the potential risks of model overfitting. The article draws conclusions about the prospects for further research, including the development of hybrid models, optimization of algorithms to reduce computational costs, and their adaptation to specific industries. The integration of artificial intelligence and operations research methods is a promising area that contributes to improving decision-making processes and provides more flexible and efficient approaches to management in today’s fast-changing world.