This paper is dealing with the solution of the hydrothermal scheduling problem by using evolutionary algorithm. The aim of this study is to minimize the fuel cost and ramping cost of thermal units by utilizing both hydro and thermal units optimally. In evolutionary programming, new generations are produced from randomly generated initial vector by Gauss and Cauchy mutations and they compete with parent vectors and each other. Better individuals are selected for the next generation. The new generation process lasts until either reach to defined iteration number or a minimum function value or the point where developed solutions are no longer different.