This paper presents an artificial bee colony algorithm for solving optimal short term hydrothermal scheduling problem. To demonstrate the effectiveness of the proposed algorithm, two hydrothermal power systems were tested. The test system 1 consists of three thermal units and four cascaded hydro power plants. In this case study, the valve point loading effect is taken into consideration. The test system 2 consists of five thermal units and one pumped storage power plant. In order to show the feasibility and robustness of the proposed algorithm, a wide range of thermal and hydraulic constraints are taken into consideration. The numerical results obtained by ABC algorithm are compared with those obtained from other methods such as genetic algorithm (GA), simulated annealing (SA), evolutionary programming (EP) and constriction factor based particle swarm optimization (CFPSO) technique to reveal the validity and verify the feasibility of the proposed method. The experimental results indicate that the proposed algorithm can obtain better schedule results with total fuel cost saving and minimum execution time when compared to other methods.