This research aims to provide a data-driven model of gas consumption management with an emphasis on the problem of unauthorized use based on the analysis of information systems. This mixed study has been done with the library research method, with metasynthesis technique in the field of gas consumption management and mathematical programming with genetic algorithm. ATLAS TI software was used for analysis. The research population, i.e. studies, articles and theses of scientific databases, was reviewed related to 2016 to 2023 were examined. 27 studies were selected based on the CASP technique. In the continuation of mathematical modeling in MATLAB software, the simulation performed with three proposed algorithms was compared. Based on the results obtained, the main categories are the use of renewable energy, gas consumption management, shortcomings, obstacles, data-driven solutions, consequences of gas consumption management and economic growth. Also, all three proposed mathematical models showed the foundation of optimal gas consumption and reduction of unauthorized consumption. The use of data analysis in the management of gas energy consumption can help to improve system efficiency, identify weaknesses and losses, increase productivity and optimize the use of gas energy. Based on the analysis, data mining can be very useful in managing gas energy consumption and simulating gas energy consumption management using a genetic algorithm can provide efficient and effective solutions, handle complex and dynamic scenarios, and offer insights into optimizing gas consumption and energy efficiency.