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An Efficient Multiobjective Optimizer Based on Genetic Algorithm and Approximation Techniques for Electromagnetic Design

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4 Author(s)
Ho, S.L. ; Hong Kong Polytech. Univ. ; Yang, S.Y. ; Ni, G.Z. ; Wong, K.F.

To provide an efficient multiobjective optimizer, an approximation technique based on the moving least squares approximation is integrated into an improved genetic algorithm. In order to use fully, both the a posteriori information gathered from the latest searched nondominated solutions and the a priori knowledge about the search space and individuals, in guiding the search towards more and better Pareto solutions, a gradient direction based perturbation search strategy and a preference function based fitness penalization scheme are proposed. Numerical results are reported to validate the proposed work

Published in:

Magnetics, IEEE Transactions on  (Volume:43 ,  Issue: 4 )

Date of Publication:

April 2007

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