This paper is concerned with the unit commitment of hydro generating units on an hourly basis throughout a single day. The performance criterion to be optimized includes the efficiency of hydro conversion, which depends on variations in tailrace elevation, penstock head losses and turbine-generator efficiency, as well as the cost of startup/shutdown of the hydro generating units. The paper presents a comparison of two heuristic approaches for solving the optimization problem. One heuristic is based on decomposing the problem into Generation Scheduling (GS) and Unit Scheduling (US) sub-problems, and solving the sub-problems by Lagrangian Relaxation and Dynamic Programming, respectively. The other heuristic makes use of a Genetic Algorithm combined with Lagrangian Relaxation to solve the original problem. The two heuristics were tested on a system composed of sixteen hydro plants, one hundred generating units, and an installed capacity of 21,933 MW in the Brazilian power system. The actual scheduling of generation actual for a typical day was used for comparison with the solutions proposed by the two heuristics. The results of both heuristics show significant savings in terms of hydro conversion efficiency and startup/shutdown costs. Soares, S., Salmazo, C., Minimum Loss Predispatch Model for Hydroelectric Power Systems (1997) IEEE Transactions on Power Systems, 12 (3), pp. 1220-1228. , AugustArce, A., Ohishi, T., Soares, S., Optimal Dispatch of Generating units of the Itaipu Hydroelectric Plant (2002) IEEE Transactions on Power Systems, 17, pp. 154-157. , FebruaryNilsson, O., Sjelvgren, D., Hydro unit start-up costs and their impact on the short term scheduling strategies of swedish power producers (1997) IEEE Transactions on Power Systems, 12, pp. 38-43. , FebrearySoares, S., Ohishi, T., Cicogna, M., Arce, A., Dynamic dispatch of hydro generating units (2003) IEEE Power Tech, Bologna, Italy, JulySoares, S., Ohishi, T., Cicogna, M., Arce, A., Optimal dispatch of hydro generating units (2004) IX Symposium of Specialists in Electric Operational and Expansion Planning, , Rio de Janeiro, May, in PortugueseSantos, E., Ohishi, T., A Hydro Unit Commitment Model Using Genetic Algorithm (2004) IEEE 2004 Congress on Evolutionary Computation, , Portland, OR, JunLuemberger, D., (1984) Introduction to Linear and Non-Linear Programming, , Second Edition, Addison-Wesley, Reading, MassDenardo, E.V., (1982) Dynamic Programming, Models and Aplications, , Prentice-HallMichalewicz, Z., Genetic Algorthm + (1996) Data Structures=Evolution Programs, , New York,Springer-VerlagOrero, S.O., Irving, M.R., A genetic algorithm modeling framework and solution technique for short term optimal hydrothermal scheduling (1998) IEEE Transactions on Power Systems, 13 (2), pp. 501-517. , MayChen, P.H., Chang, H.C., Genetic aided scheduling of hydraulic coupled plants in hydro-thermal coordination (1996) IEEE Transactions on Power Systems, 11 (2), pp. 975-981. , MayYiying, Z., Feng, W., Xiaomin, B., Unit commitment problems using GA (2002) IEEE-PES 2002 Summer Meeting, , Chicago, JulyArroyo, J.M., Conejo, A.J., A parallel repair genetic algorithm to solve the unit commitment problem (2002) IEEE Transactions on Power Systems, N (4), pp. 1216-1224. , NovemberMantawy, A.H., Abdel-Magid, Y.I., Selim, S.Z., A new genetic algorithm approach for unit commitment (2002) IEEE-PES 2002 Summer Meeting, , Chicago, July