This study aimed to develop and enhance a Genetic Algorithm (GA) method to optimize and maximize weekly hydropower generation for a single reservoir. In this study GA approach significantly improves hydropower generation efficiency by optimizing water usage for reliable electricity production, better flood control, and improved irrigation water supply. Compared to traditional methods, this approach offers a more dynamic and adaptable solution, potentially leading to higher energy output and better resource management. The Karun Reservoir Dam is a significant multipurpose project that addresses several critical needs, including electricity generation, flood control, and water supply for irrigation. In this study presents time series data for optimizing the operation of the Karun reservoir, located in Iran, over a period of 13.5 years from January 2010 to June 2023. The time-series data includes reservoir inflow, reservoir storage, no evaporation, minimum environmental flow requirement, and minimum weekly power load requirement (given as average operating power per week in MW). The maximum flow through the hydropower is influenced by the storage and release of water through the power plant. The data analyzes a model based on the GA for the optimization of water resources. The analysis revealed that on population size 100, generation 1000, and mutation rate 0.1, the GA achieved the best solution of the objective function is 1865861871055.71.