This paper describes a method for scheduling large-scale hydrothermal power systems based on the shuffled complex evolution (SCE-UA) method. A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is also taken into account. SCE-UA is a successfully proven method in global optimization for many situations. Benefiting from its unique global optimization strategies into the inverse procedure greatly enhances the performance of SCE-UA method since it can not only effectively locate the promising areas in the solution space for a global minimum but also avoid its wandering near the global minimum in the final stage of search. The efficiency of the SCE-UA method is analyzed in terms of the mean performance and computational time, in comparison with the particle swarm optimization (PSO) algorithm. The simulation results reveal that SCE-UA effectively overcomes the premature phenomenon and improves the global convergence and optimization searching capability. It is a relatively consistent, effective and efficient optimization method in solving the large scale hydrothermal scheduling problem.