This paper proposes an efficient method to solve the profit-based optimal self-scheduling of a hydroelectric company in the pool-based day-ahead electricity market by integrating cultural algorithm (CA) with feasible sequential quadratic programming (SQP). The proposed method is developed in such a way that CA is applied as a based level search, which can give a good direction to the optimal global region, and a local search SQP is used as a fine-tuning to determine the optimal solution at the final. Finally, optimal self-scheduling of hydro company with several cascaded hydro plants along a river basin is used to illustrate the effectiveness of the proposed method. Results from the proposed method are compared with those obtained by other optimization methods in terms of solution precision. It is shown that the proposed method is capable of yielding higher quality solutions. (C) 2010 Elsevier Ltd. All rights reserved.