Genetic Algorithm and Breeding: GA 1960s first proposed by the University of Michigan, USA JHHolland professor [1]. It can be widely used in artificial intelligence, machine learning, optimization, automatic control functions. The salient features of the GA is the solution space of the problem by transcoding the GA search space, the solution of the problem of biological individuals, and with the help of bio-genetic and evolutionary theory, multiple individual selection, crossover and variation operation. In this way, you can quickly search for the optimal solution. However, the genetic algorithm is easily trapped into local optima. Search efficiency is not

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GNew_Genetic_e

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