An Adaptive Evolutionary Algorithm for Numerical Optimization
نویسندگان
چکیده
In this paper, a normalized oating point representation has been used for making it be possible to design biotechnical genetic operators as well as to apply some genetic operators like inversion. To improve the adaptation of evolutionary algorithms and avoid the biases which may exist in some genetic operators, we have designed and applied several kinds of genetic operators with some probability. The experimental results show that our adaptive evolutionary algorithm has a better performance than the BGA (Breeder genetic Algorithm) and GAFOC (Genetic Algorithm For Optimal Control problems) for the test problems .
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