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This article presents a new, improved particle swarm optimization algorithm with a selection operator for the solution of the combined heat and power economic dispatch problem. In this technique, starting with a large swarm of particles, only those particles whose fitness is above the scaled average fitness are selected in successive iterations, using a selection factor that is adjustable depending on the nature of the problem. The method is illustrated using a test case. The result compares favorably with other particle swarm optimization variants and other existing non-conventional methods.

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