The article deals with the problem of adaptation of the Russian oil and gas company (Novatek, Russia) to the rapidly changing external environment, the avalanche of data from competitors, and the need to filter important information for business development and the prosperity of the industry as a whole. The approach is based on the system of integrated software monitoring of key business processes at the enterprise developed by the authors—from the formation of the idea of a new product to its implementation to paying customers. The scientific novelty lies in the use of an optimization model that allows for minimizing the maximum losses of the investor at all levels of decision-making, from the distribution of capital between companies, to the optimization of internal reserves to increase the competitiveness of the company. The toolkit is a minimax model that allows you to redistribute the shares of investor influence at the portfolio level, and then within the business processes of each company selected by investors, in order to achieve the optimal solution in accordance with the selected estimated indicators. Application of the well-known portfolio investment models of Markowitz, Tobin, Sharp, etc. is not possible due to the lack of necessary data on the basis of which the probabilistic parameters involved in the model are estimated. Even if we get them, it is necessary to take into account the level of correlation influence of the technological process in the composition of each subsystem, which is unacceptable for the data used, as it leads to a strong increase in errors. Using minimax and a systematic approach allows you to minimize such errors by choosing a balanced concentration of distributed assets for both the investor and the buyer. To this end, a three-way analysis of the company’s development was carried out and a technology for comprehensive improvement of the company’s activities was developed in the following areas: the company’s rating in the industry, financial condition, and interaction with counterparties using merchandising technologies. Tools for optimal image zoning at the Novatek site using the minimax approximation criterion have been developed. The technology provides a procedure for creating a comfortable mode of image perception based on high-tech visualization of merchandising, zoning of the screen area, and a mathematical approach that allows you to develop a calculation algorithm.

A model has been developed for the optimization of the share structure of an investment portfolio in high-tech projects supported by the leaders of the leading industry companies in Russia. Several indicators (financial leverage, integrated rating of companies, industry rating) were applied in the decision support system for the shared distribution of investments. High-tech production is based on innovative technologies for saving resources, the resiliency of systems for transporting and transferring raw materials and finished products within Russia, so the main income will remain within the country. It is possible to export high-tech products, rather than raw materials, which will increase export revenues. Investors will invest in high-tech projects of Russian companies, taking into account the targeting of investment development. The guarantee is the stable financial position of the companies and the competitiveness rating. Methods: The authors propose a new approach that does not contradict modern rating scales, based on a hierarchical rating procedure and fuzzy logical rules that allow you to build an integral rating in the form of portfolio shares from the whole. A higher share shows an indicator of the higher investment attractiveness of companies. The industry rating is obtained based on the principle of the company’s first affiliation to the highest rating indicator. The final minimax portfolio is based on the initial ratings in a circular convolution and is then adjusted by industry. A software package has been compiled that allows the testing of the method of capital allocation between investment projects for the largest companies’ leaders of high-tech industries in Russia. This software uses the author’s method of multi-stage analysis, the evaluation of financial coefficients, the integral ranking and the correction of the solution taking into account the industry attributes. Results: The results are presented with computer-aided design (CAD) in the form of an algorithmized decision support system (DSS). The CAD system is based on a hierarchical algorithm, based on the use of a multi-level redistribution of investment shares of high-tech companies, taking into account the adaptation to the requirements of the return on investment portfolio. When compiling the portfolio, the minimax optimality criterion is applied, which allows the stabilization of the risk by purposefully redistributing funds between the companies involved in the analysis. The authors of the article have compiled an algorithm for the software implementation of the model. Features of the rating approach: the use of the author’s mathematical apparatus, which includes a hierarchical analysis of the ranked indicators of the financial and economic activity of companies, taking into account their priority, and the use of a minimax approach to obtain a rating assessment of companies, taking into account the industry attributes. Development: The proposed approach should be used for targeted financing of large industry companies engaged in the implementation of high-tech projects.

In the context of global economic instability, the problem of ensuring food security and sustainable development of agriculture at the international, national and regional levels becomes urgent. Existing methods for assessing the state of food security and sustainable development of agriculture, as a rule, have two main drawbacks: first, they are often static, and second, they include a scattered list of indicators that are difficult to systematically interpret in the analysis. Therefore, theaimof the study is to develop an adequate methodology for assessing the food security of the constituent entities of the Russian Federation. The construction of a thematic index is carried out in three stages: 1) a system of indicators is formed; 2) the values of indicators are normalized; and 3) sub-indices are calculated. The analysis of domestic and foreign literature on food security provided themethodological basisof the study. The system of indicators was clarified, which were combined into three groups (numerical indicators of the sphere of production, distribution, consumption, and food). The authors extended the retrospective assessment of food security at the meso-level by ranking and clustering Russian regions using hierarchical analysis and a new data filtering algorithm. The hierarchical procedure is based on a system of mathematical filtering of data, which is fundamentally different from existing methods for analyzing hierarchies. The authors replaced the fuzzy “what if” logic with a clear subordination of ranked indicators (subindices). The group of leaders was selected considering the accepted priority of indicators, the rest of the regions were united into a new subgroup, among which leaders and outsiders were singled out. At each new stage, new groups are ranked after excluding leaders and outsiders, they are in the “center of the circular convolution of data”, the procedure for stopping the procedure is the presence of two groups. This is a fundamental feature, scientific novelty, and value of the mathematical apparatus for multidimensional ranking of Russian regions in terms of food security. The authorsconcludedthat in modern Russia the problem of food security has not yet been resolved due to the insufficient use of general economic and special levers to increase the stability of the food system. The results of the study can be applied in the process of updating the state policy in the field of ensuring the sustainability of food systems at the macroand meso-level of management.

The authors propose an instrumental apparatus for calculating the ratings of Russian companies in the oil and gas and electric power industries based on a weighting method, risk assessment using the minimax criterion and an intellectual tree structure. The relevance of the developed system is justified by the need to create Russian rating systems for companies that will represent their actual state and place in the analyzed group. The problem of data redundancy has been solved by using the hierarchical principle for the isolated indexing of absolute and relative indicators from the financial statements of the companies in question into sub-indexes, with further integral indexing and correction for the volatility of changes over the past three years. The authors used a financial analytics apparatus based on the regular financial (accounting) statements of companies according to accepted forms, and balance sheets and reports on financial results were applied. The authors developed and tested a methodology for sub-indexing important indicators of financial statements: capital structure—equity, debt capital, highly liquid assets (cash and settlement accounts in reliable banks, short-term financial investments) and net profit. Based on the results of the analysis, recommendations are provided for the long-term development of the energy business.