PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Chiaradonna S., Di Giandomenico F., Murru N. On enhancing efficiency and accuracy of particle swarm optimization algorithms. In: International Journal of Innovative Computing, Information & Control, vol. 11 (4) pp. 1165 - 1189. ICIC International, 2015.
 
 
Abstract
(English)
The particle swarm optimization (PSO) algorithm has been re- cently introduced in the non{linear programming, becoming widely studied and used in a variety of applications. Starting from its original formulation, many variants for improvement and specialization of the PSO have been already proposed, but without any definitive result, thus research in this area is nowadays still rather active. This paper goes in this direction, by proposing some modifications to the basic PSO algorithm, aiming at enhancements in aspects that impact on the efficiency and accuracy of the optimization algorithm. In particular, variants of PSO based on fuzzy logics and Bayesian theory have been developed, which show better, or competitive, performances when com- pared to both the basic PSO formulation and a few other optimization algorithms taken from the literature.
URL: http://www.ijicic.org/contents.htm
Subject Fuzzy logics
Kalman filter
Non-linear programming
Particle swarm optimization
G.1.6 NUMERICAL ANALYSIS. Optimization


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