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For the large-scale electromagnetic problems, the existing optimization methods normally cannot search for a global optimal solution in the design space accurately and have a lower numerical efficiency. In order to mitigate these problems, this paper presents a novel optimal design algorithm based on the subdivision strategy. In the proposed algorithm, first, the whole design space is decomposed into...
This paper presents a global optimization algorithm combining an adaptive response surface approximation of the objective function and (1+λ) evolution algorithm. In the adaptive approximation, an optimal Latin hypercube sampling strategy based on multi-objective Pareto optimization is developed to obtain the sampling data in the design variable space, and multiquadric radial basis function is employed...
A global optimization algorithm combining an adaptive response surface approximation of the objective function and experiment design strategy is presented. In the adaptive approximation, an optimal Latin hypercube sampling strategy based on multi-objective Pareto optimization is developed to obtain the sampling data in the design variable space, and multiquadric radial basis function is employed to...
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