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|Title:||An efficient multiobjective optimizer based on genetic algorithm and approximation techniques for electromagnetic design|
Wong, K. F.
Genetic algorithm (GA)
|Source:||IEEE transactions on magnetics, Apr. 2007, v. 43, no. 4, p. 1605-1608.|
|Abstract:||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.|
|Rights:||© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
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|Appears in Collections:||EE Journal/Magazine Articles|
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