Improved Particle Swarm Optimization algorithms for electromagnetic optimization

Issue title: Soft Computing and Applications

Article type: Research Article

Authors: Mussetta, Marco | Selleri, Stefano | Pirinoli, Paola | Zich, Riccardo E. | Matekovits, Ladislau

Affiliations: DEE, Politecnico di Milano p. Leonardo da Vinci 32 – 20133 Milano, Italy. E-mail: marco.mussetta@polimi.it, riccardo.zich@etec.polimi.it | DET, University of Florence Via C. Lombroso 6/17 50134 Florence, Italy. E-mail: stefano.selleri@unifi.it | DEE, Politecnico di Torino, c. Duca degli Abruzzi 24, 10129 Torino, Italy. E-mail: {paola.pirinoli,ladislau.matekovits}@polito.it

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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.

Keywords: Genetic algorithm, particle swarm, optimization

Journal: Journal of Intelligent & Fuzzy Systems, vol. 19, no. 1, pp. 75-84, 2008