The paper presents the structure of the optimal Decision Support System (DSS) for planning, preparing and implementation of nuclear facilities decommissioning. The proposed structure is intended to implement the following DSS functions: modelling of nuclear facilities and decommissioning activities carried out according to various possible decommissioning options; quantitative assessment of a specific set of partial indicators that characterise the possible decommissioning strategies; identifying the preferences of the decision-maker and redacting them to a formalised form (the quantitative restrictions on the values of partial indicators, the weighting functions of significance for partial indicators); identification of the values of the complex indicator which is a measure for optimality of the considered possible decommissioning strategies. Possible decommissioning strategies are described using a set of the following partial indicators: potential radiation hazards, decommissioning costs, duration of the decommissioning stage. The DSS is designed to be used for decommissioning of nuclear facilities in the Russian Federation. However, it can be used for decommissioning of nuclear facilities in other countries after appropriate modifications.

This paper is devoted to the development of mathematical models of exhaustion process of extracted mineral resources. Our new model combines the advantages of previous models and is devoid of their disadvantages. The model uses the transition of the growth rate of extraction of mineral resource to stationary value. The initial known parameters of the model include the explored residual volume of the mineral resource, the initial volume of its extraction, the initial growth rate of its extraction, and the indicator of decreasing rate of extraction growth. The model is applied using the example of predicted extraction and exhaustion of natural uranium.

Protecting information that is potentially accessible through external communication channels from external threats is one of the primary objectives of information security. Creating an information security system requires material investments, the cost of which increases along with the increasing degree of information protection. Therefore, the task of determining the level of investment in information security that provides the minimum total cost of the information protection system and losses from realized threats that remain after the implementation of the information protection system arises. In this paper, we present a scheme that allows us to solve the problem of optimizing the costs of an information security system, the implementation of which ensures a minimum of average total costs for the implementation of the information security system and losses due to the remaining threats realized after the establishment of information security system.

The problems of efficient allocation of resources in the areas of the company activity under conditions of uncertainty are considered. The indicators of effectiveness in the areas of the company activity are of an uncertain nature and are random variables with predetermined laws of probability distribution. To form an effective distribution of the company’s activities in the areas of its activities, a scheme is used to form effective portfolios based on the probabilities of priority developed at the NRNU MEPhI. As estimates of the values of the efficiency index for the directions of the company’s activities, their forecasts were taken as random variables with a uniform or normal probability distribution law.

Problems for shares of resources to be distributed in conditions of constraints, including the process of dynamic change of shares are considered. The tasks of forming and dynamically changing the composition of portfolios are considered, in particular, in the presence of group restrictions. A mathematical model for predicting the dynamics of shares for a transition process from one equilibrium state of the system to another equilibrium state is proposed. The case of the presence of a noise chaotic component in such a model is considered. An example of the application of the proposed model of the dynamic process of resource allocation is given.

The International Nuclear Management Academy (INMA) is an IAEA facilitated collaboration framework in which universities provide master’s degree programmes focusing on the management aspect for the nuclear sector. The INMA targets current and future managers working in the nuclear energy and nuclear non-power application sectors. The purpose of the INMA is to improve the safety, performance and economics of nuclear technologies by promoting and enabling the availability and accessibility of consistent high quality educational opportunities for nuclear sector managers and improving their management competencies. The paper presents experience of implementation of INMA Master’s Program at the National Research Nuclear University MEPhI.

The paper presents a mathematical model of efficient portfolio formation in the reinsurance markets. The presented approach provides the optimal ratio between the expected value of return and the risk of yield values below a certain level. The uncertainty in the return values is conditioned by use of expert evaluations and preliminary calculations, which result in expected return values and the corresponding risk levels. The proposed method allows for implementation of computationally simple schemes and algorithms for numerical calculation of the numerical structure of the efficient portfolios of reinsurance contracts of a given insurance company.

This report introduces two approaches to the efficient portfolio selection problem, wherein the criteria and the constraints are linear with respect to control variables. The first approach consists of unconditioned optimization of the average expected efficiency value of a portfolio without imposing any additional constraints on the structure of selected portfolio. For this scheme the problem of effective portfolio formation is reduced to two linear programming problems, solving these for an efficient frontier may be effectively accomplished in closed form. The second scheme considers an additional set of group constraints, which can also be reduced to the problem of finding the Pareto fronts of two linear programming problems.