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An efficient and optimum economic operation and planning of electric power generation systems is very important. The basic requirement of power economic dispatch (ED) is to generate adequate electricity to meet load demand at the lowest possible cost under a number of constrains. Genetic Algorithms (GA) represents a class of general purpose stochastic search techniques which simulate natural inheritance by genetics. In this paper, the principles of genetics involving natural selection and evolutionary computing applied for producing an economic dispatch. By simulating “Survival of the fittest” among chromosomes, the optimal chromosome is searched by randomized information exchange. In every generation a new set of artificial chromosomes is created using bits and pieces of the fittest of old ones while randomized.