Title :
On simultaneous perturbation particle swarm optimization
Author :
Maeda, Yutaka ; Matsushita, Naoto ; Miyoshi, Seiji ; Hikawa, Hiroomi
Author_Institution :
Dept. of Electr. & Electron. Eng., Kansai Univ., Suita
Abstract :
In this paper, we describes the simultaneous perturbation particle swarm optimization which is a combination of the particle swarm optimization and the simultaneous perturbation optimization method. The method has global search capability of the particle swarm optimization and local search one of gradient method by the simultaneous perturbation. Some variations of the method are described. Comparison between these methods and the ordinary particle swarm optimization are shown through five test functions and learning problem of neural networks.
Keywords :
gradient methods; neural nets; particle swarm optimisation; search problems; global search capability method; gradient method; neural networks; simultaneous perturbation particle swarm optimization; Educational technology; Finite difference methods; Gradient methods; Neural network hardware; Neural networks; Optimization methods; Particle swarm optimization; Perturbation methods; Stochastic processes; Testing;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983359
