Please use this identifier to cite or link to this item:
|Title:||An efficient multiobjective optimizer based on genetic algorithm and approximation techniques for electromagnetic design|
|Authors:||Ho, SL |
Genetic algorithm (GA)
|Source:||IEEE transactions on magnetics, Apr. 2007, v. 43, no. 4, p. 1605-1608 How to cite?|
|Journal:||IEEE transactions on magnetics|
|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.|
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
|Appears in Collections:||Journal/Magazine Article|
Show full item record
Citations as of Feb 6, 2016
WEB OF SCIENCETM
Citations as of Feb 5, 2016
Checked on Feb 7, 2016
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.