This paper present short-term combined economic and emission hydrothermal optimization, addressing total fuel costs and emissions minimization. This paper uses the fuel cost function with valve-point effect, which increases the degree of optimization problem difficulty. The optimal balance between the addressed objectives, that conflict with each other, can be obtained with appropriate hydro and thermal generation schedules. A surrogate differential evolution is applied in order to satisfy 24-h system demand and final states of hydro power plant reservoirs by minimized total fuel costs and emissions. This paper proposes a novel master–slave model optimization algorithm, where the optimal thermal schedules are obtained within the slave model. The data obtained from the slave model are saved into a matrix, which serves as a surrogate model for a master model, where the hydrothermal optimization with all objectives and constraints is conducted by using a parallel self-adaptive differential evolution algorithm. In order to show the effectiveness of the proposed method, different case studies are used: economic load scheduling, economic emission scheduling, and combined economic emission scheduling. The proposed method is verified on a model consisting of four hydro power plants and three thermal power plants.