MULTICRITERIA TASK OF FORMING GENERATIONS OF NEW TECHNOLOGY

The purpose of the study. It is noted that the priority direction of economic development is innovation, and this implies the organization of work on the formation of generations of new technology. This circum-stance is caused by a number of factors. It is shown that in the course of solving these problems, the most promising methods are the multi-criteria description of the problem. Hence, there is a need to reduce the methods of multi-criteria optimization in relation to the tasks formation of new generations of technology. The complexity of the process of developing innovative solutions that ensure accounting is noted technological, economic and environmental factors. A formal statement of the problem of choosing technologies that maximize revenue within the allocated budget with a minimum number of selected solutions is given. Materials and methods. Methods for solving multi-criteria problems are considered, including the classical method of branches and boundaries, dynamic programming, greedy and heuristic algorithms, hierarchy analysis, the assignment method, evolutionary algorithms and the Pareto method. Special attention is paid to the formation of a Pareto-optimal set, which makes it possible to reduce the number of alternatives by eliminating inefficient solutions. It demonstrates how discretization of the cost interval and solving a series of integer programming problems generate points on the Pareto curve. Results. The practical significance of the research is explained by the needs in the course of construction project management, where optimization reduces costs, and antimonopoly regulation through the analysis of graphs of market interactions. Recently, there has been widespread use of PLM systems and artificial intelligence in improving the efficiency of such developments. At the same time, the problem of creating environmentally friendly technologies should not be left out. Conclusion. The need to integrate mathematical models with modern management tools is emphasized in order to minimize subjectivity in decision-making. The use of multi-criteria models, machine learning methods, and adaptation of approaches to non-Markov processes is considered a prom-ising area. It is shown how the transition from a multi-criteria task to a sequence of traditional optimization tasks is possible. It is emphasized that in this case, a Pareto-optimal set of solutions to the problem under consideration is constructed.