The solution of generation scheduling (GS) problems\ud involves the determination of the unit commitment (UC) and\ud economic dispatch (ED) for each generator in a power system at\ud each time interval in the scheduling period. The solution\ud procedure requires the simultaneous consideration of these two\ud decisions. In recent years researchers have focused much\ud attention on new solution techniques to GS. This paper proposes\ud the application of a variety of genetic algorithm (GA) based\ud approaches and investigates how these techniques may be\ud improved in order to more quickly obtain the optimum or near\ud optimum solution for the GS problem. The results obtained show\ud that the GA-based hybrid approach offers an effective alternative\ud for solving realistic GS problems within a realistic timeframe
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