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Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
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机译:结合基于模型和基于遗传的后代,使用收敛准则进行多目标优化
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摘要
A system and method for combining the model-based and genetics-based methods are combined according to a convergence criterion. When the population is not converged, the genetics-based approach is used, and when the population is converged, the model-based method is used to generate offspring. The algorithm benefits from using a model-based offspring generation only when the population shows a certain degree of regularity, i.e., converged in a stochastic sense. In addition, a more sophisticated method to construct the stochastic part of the model can be used. Also a biased Gaussian noise (the mean of the noise is not zero), as well as a white Gaussian noise (the mean of the noise is zero) can be preferably used for the stochastic part of the model.
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