Description: Double elite co-evolutionary genetic algorithm to learn the elite strategy and the thought of cooperative coevolution, choose two dissimilar, high fitness individuals (elite individual) as the core of evolutionary operation, two elite individuals respectively according to different uation function to choose the individual, of their own, anti-fuzzy into populations. Two child population respectively in different evolutionary strategy, in order to balance the exploration and search ability of the algorithm.
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DECGA
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