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The genetic algorithm is a search procedure based on the mechanics of natural selection and natural genetics, which combines an artificial survival of the fittest with genetic operators abstracted from nature. In this paper, a genetic algorithm for function optimization is introduced and applied to calibration of a conceptual rainfall‐runoff model for data from a particular catchment. All seven parameters of the model are optimized. The results show that the genetic algorithm can be efficient and robust.
Quan J. Wang (Sun,) studied this question.