Research of Function Optimization Algorithm
Abstract
Traditional evolutionary algorithm trapped into the local minimum easily. Therefore, based on a simple evolutionary algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, crossover operator, as well as the introduction of Inver-Over operator to prevent local convergence to form a new evolutionary algorithm. Through the series of numerical experiments, the new algorithm has been proved is efficiency for function optimization.
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