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Economic dispatch is one of the important problems in the operation of electric power system. The purpose of this paper is to determine optimal generation scheduling with minimum fuel costs. The proposed fuzzified particle swarm optimization algorithm is a combination of fuzzy logic incorporated in the particle swarm optimization algorithm. In this paper, the performance of the fuzzified particle swarm optimization algorithm is compared with the conventional method, the lagrange multiplier method. 6 thermal power plants are used as input data for simulation. The results show that the proposed method can provide a more accurate solution and has the potential to be applied to other electric power system optimization problems.