Improved Particle Swarm optimization algorithms for electromagnetic optimization

Marco Mussetta*, Stefano Selleri, Paola Pirinoli, Riccardo E. Zich, Ladislau Matekovits

*Corresponding author for this work

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function and to a microwave microstrip filter to show their superior capabilities with respect to the conventional version.

Original languageEnglish
Pages (from-to)75-84
Number of pages10
JournalJournal of Intelligent and Fuzzy Systems
Volume19
Issue number1
Publication statusPublished - 2008
Externally publishedYes

Keywords

  • Genetic algorithm
  • Optimization
  • Particle swarm

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  • Cite this

    Mussetta, M., Selleri, S., Pirinoli, P., Zich, R. E., & Matekovits, L. (2008). Improved Particle Swarm optimization algorithms for electromagnetic optimization. Journal of Intelligent and Fuzzy Systems, 19(1), 75-84.