The energy overconsumption at drinking-water pumping stations creates considerable energy losses. For this reason we have developed an NNGA tool of pumping management which optimizes the consumed energy by the pumping system with respect to the hydraulic functioning conditions in the distribution tank. This tool includes two models: a forecasting model for drinking water demand based on artificial neural networks and an optimization model using genetic algorithms. The results of the NNGA tool were compared with two pumping plans: the plan based on the pumping regulation model, and the plan used by the company of water and sewage of the city of Algiers. The analysis result was done with the help of performed indicators that we have developed and which enable the evaluation and diagnosis of the energetic function's system.