Optimization in electromagnetics using the real-coded clonal selection algorithm

Felipe Campelo*, Frederico G. Guimarães, Jaime A. Ramírez, Hajime Igarashi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work analyzes the Real-coded Clonal Selection Algorithm (RCSA) for mono objective optimization in electromagnetics. This algorithm presents a set of features enabling global search as well as the local improvement of the candidate solutions. An analysis of the sensitivity of the algorithm to its basic parameters shows that it is possible to suggest a basic configuration for the RCSA, narrowing the range of variation of the input parameters and simplifying the use of the algorithm. Results obtained on a test problem show that this algorithm is able to find higher-quality solutions, and also presents fasterconvergence than similar approaches for the problem considered.

Original languageEnglish
Title of host publicationSMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications
PublisherIEEE
Pages89-94
Number of pages6
ISBN (Print)9781424437825
DOIs
Publication statusPublished - 1 Dec 2008
Event2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08 - Muroran, Japan
Duration: 25 Jun 200827 Jun 2008

Conference

Conference2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08
CountryJapan
CityMuroran
Period25/06/0827/06/08

Keywords

  • Artificial immune systems
  • Electromagnetics
  • Optimization and design

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  • Activities

    • 1 Participation in conference

    2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08

    Felipe Campelo Franca Pinto (Participant)

    2008

    Activity: Participating in or organising an event typesParticipation in conference

    Cite this

    Campelo, F., Guimarães, F. G., Ramírez, J. A., & Igarashi, H. (2008). Optimization in electromagnetics using the real-coded clonal selection algorithm. In SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications (pp. 89-94). [5045941] IEEE. https://doi.org/10.1109/SMCIA.2008.5045941