Analytical Modeling and Genetic Algorithms in the Development of Adaptive Strategies for Optimizing Energy Efficiency of the Fuel and Energy Complex (Case of the Regions of China, Russia and India)
Year: 2026
Type: article
Abstract: This study is devoted to the development of an algorithm for analyzing and optimizing energy efficiency indicators in the fuel and energy complex (FEC) based on state statistics of the leading BRICS economies (China, Russia and India).The research methodology includes formalization of key factors influencing energy saving targets, construction of econometric models, cleaning variables from statistically insignificant factors and application of genetic algorithms to determine optimal parameters.The final optimization function implements mathematical formalization of the compromise between increasing energy efficiency targets and minimizing changes in input factors, which makes the results suitable for practical implementation.The algorithm provides solutions that minimize costs and ensure compliance with the specified constraints within the modeling framework.The final data are presented in the form of text reports and infographics, allowing for a detailed statistical and analytical review of the indicators by region of the countries considered.This aspect allows integrating the obtained results into the process of making economically sound strategic decisions aimed at modernizing and improving the efficiency of the energy sector.The developed approach is focused on current tasks of strategic management, including data systematization, development of long-term programs for modernization of the fuel and energy complex and increasing the sustainability of the energy system to external factors.The results obtained have a high degree of universality and can be applied to optimize individual processes within the energy sector and to develop national and interstate energy saving strategies.
Source: MONTENEGRIN JOURNAL OF ECONOMICS
Author: DMITRY RODIONOV
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7147574896
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