The paper presents the results of the developed algorithms aimed at optimizing management decision-making by the administration of megalopolises. A mathematical model is obtained within the concept of digital economy. The regulatory action of dispositive decisions is aimed at business entities whose activities are externalized while consuming energy resources. Since any resources are used unevenly throughout the year, the authors apply the methods of the theory of optimal decisions. The criterion is the functional reflection of the balance between the maximum profit, the comfort of living conditions, and the environmental conditions. The results obtained make it possible to take administrative decisions in an optimal way, which reduces the negative effects of externalities and results in the most efficient use of energy resources.
The life of a contemporary person acquires a new quality due to smart solutions, hence the issue of what affects the appearance of smart solutions and what impact smart solutions have on economic activity indicators is relevant. The paper is aimed at identifying correlations between urban logistics and infrastructure digitalization and a Gross Domestic Product size. This paper explores the most popular digital solutions that affect the quality of logistics and infrastructure. This paper shows that a rather significant correlation is observed between the logistics and infrastructure digitization indices and the Gross Domestic Product indices adjusted for per capita purchasing power parity. This paper demonstrates that the higher logistics and infrastructure digitization contributes to the cost rising of domesticmanufactured products. Conversely, the higher Gross Domestic Product level raises the possibility to create the more advanced and high-quality digital logistics and infrastructure. The authors concluded that the identified correlation is missing in countries having the highest gross domestic product indices adjusted for per capita purchasing power parity and their indices of digital logistics and infrastructure development are at a medium level.
Achieving energy security by preventing and timely eliminating the consequences of accidents at energy facilities and in energy supply systems of enterprises is one of the important tasks of energy management. The basis for planning appropriate energy security measures is the prediction of damage from these accidents. The purpose of forecasting is to assess the possibility of an accident occurring at some point in time and leading to a particular damage, and to assess the magnitude of this damage. The article proposed methodological approaches to the construction of mathematical models of such prediction. In this case, as an indicator of damage, the economic losses caused by these accidents are taken. The simulation is based on the representation of this indicator in the form of a step change function of the magnitude of losses in the event of an accident. Depending on the amount of information available in the period prior to forecasting, the mathematical representation of the forecasting problem is reduced to the construction of conditionally determined or stochastic models. Conditionally determined models allow obtaining acceptable damage estimates with a short period of retrospection and small amounts of information, and stochastic models with significantly large amounts. At the same time, the principle of “maximum uncertainty” formalized in the form of maximum entropy is the basis for removing uncertainty in the construction of both conditionally determined and stochastic models. Its use has allowed increasing the objectivity of forecasts by minimizing the subjective information used in modeling. The proposed approaches to the construction of mathematical models for predicting accidents at energy facilities and power supply systems of enterprises are the basis for creating specific techniques for solving relevant energy management tasks both at the micro level at the scale of individual enterprises and at the macro level at the scale of industries, regions and the state as a whole.
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