Suchergebnisse

The article presents a dynamic system, a controlled dynamic economic and mathematical model in the presence of risks for the processes of organization and implementation of the university specialists training management. The system is defined by parameters describing the state of the process of training specialists with higher education, as well as the number of technologies for organization and implementation of the training process and the number of risks (a priori indefinite disturbances) during the organization and implementation of the process of training specialists with higher education at a university. © 2020 American Institute of Physics Inc. All rights reserved. ; The research is Supported by the Act 211 of the Government of the Russian Federation, agreement № 02.A03.21.0006».

The article explores the problem of optimising university training structure to increase focus on the labour market. The proposed solution is constructed using a deterministic approach in which the following vectors are formed: the phase vector, whose coordinates are the values of the parameters describing the training process in higher education institutions at a certain fixed point in time; the controlling action vector (control vector) that allows influencing (by means of funding, the school-leaving exam score required for admission and other parameters) the structure, volume and quality of university training on various degree courses (educational programs), as well as the corresponding deterministic restrictions. The construction of the optimisation model is realised in two stages. At the first stage, a discrete dynamic model is formed that describes the influence of the control vector on the parameters of the system parameters phase vector. At the second stage, restrictions are formed on the parameters of the mathematical model that take into account the labour market demand for university graduates, and the quality criteria (functionals) that allow evaluating the process under consideration at a set final point in time. © 2018 ; Government Council on Grants, Russian Federation ; The research was supported by «Act 211 of the Government of the Russian Federation, agreement № 02.A03.21.0006».