Particle swarm optimization: surfing the waves

Author

Ozcan, Ender ; Mohan, Chilukuri K.

Author_Institution

Dept. of Inf. & Comput. Sci., Yeditepe Univ., Istanbul, Turkey

Volume

3

fYear

1999

fDate

1999

Abstract

A new optimization method has been proposed by J. Kennedy and R.C. Eberhart (1997; 1995), called Particle Swarm Optimization (PSO). This approach combines social psychology principles and evolutionary computation. It has been applied successfully to nonlinear function optimization and neural network training. Preliminary formal analyses showed that a particle in a simple one-dimensional PSO system follows a path defined by a sinusoidal wave, randomly deciding on both its amplitude and frequency (Y. Shi and R. Eberhart, 1998). The paper takes the next step, generalizing to obtain closed form equations for trajectories of particles in a multi-dimensional search space

Keywords

evolutionary computation; psychology; random processes; search problems; closed form equations; evolutionary computation; formal analyses; multi-dimensional search space; neural network training; nonlinear function optimization; one-dimensional PSO system; optimization method; particle swarm optimization; particle trajectories; sinusoidal wave; social psychology principles; surfing; Computer science; Educational institutions; Equations; Frequency; Genetic algorithms; Marine animals; Optimization methods; Organisms; Particle swarm optimization; Psychology;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on

Conference_Location

Washington, DC

Print_ISBN

0-7803-5536-9

Type

conf

DOI

10.1109/CEC.1999.785510

Filename

785510