Abstract
The optimal regional budget allocation problem is examined in this article, with consideration given to public opinion, strategic priorities, ROI, and long-term sustainability. A mathematical model with two tiers is suggested, with the first tier overseeing the transfer of budget across districts and the second tier managing distribution among sectors within districts. Genetic algorithms (GA) and dynamic programming (DP) are used for optimization. Data from Kazakhstan's Almaty region for the years 2022–2024 were used to evaluate the model. Five criteria - utility, inter-district discrepancy, deviation from strategic goals, stability, and computation time were used to conduct a comparative analysis. Although DP achieves the maximum total utility (up to 114.84 conventional units), it also deviates from strategic shares by up to 1.58 and has an inter-district difference of up to 1.25×10¹¹ tenge. GA, on the other hand, offers nearly perfect alignment with strategic goals (deviation of 0.03) and 2.5 times smaller disparity, although having lower utility (on average, 4–5% below DP). GA is five times faster than DP, with a constant computation time of 56 seconds. While DP is appropriate for long-term forecasting scenarios, the acquired results validate the applicability of GA in actual digital public administration situations. The created approach can be applied to participatory budgeting and decision support systems.