论文信息 - Probability of improvement methods for constrained multi-objective optimization

Probability of improvement methods for constrained multi-objective optimization

This paper shows how the simultaneous consideration of multiple Kriging models can lead to useful metrics for the selection of design vectors in constrained multiobjective optimization. The savings in computational cost with such methods make them particularly useful for optimal electromagnetic design.

Jan K. Sykulski | G. I. Hawe

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