A new method for improving particle swarm optimization algorithm (TriPSO)

Author

Qais, Mohammed ; AbdulWahid, Zeyad

Author_Institution

Electr. Eng. Dept., King Saud Univ., Riyadh, Saudi Arabia

fYear

2013

fDate

28-30 April 2013

Firstpage

1

Lastpage

6

Abstract

In this paper, we introduced some modifications in the standard particles swarm optimization algorithm to get better results. We modified the velocity equation by inserting triangular functions (cosine and sine), increasing inertia weight and introducing a new method to avoid the stagnation problem. The modified algorithm named as Triangular Particle Swarm Optimization (TriPSO) was tested by five well-known benchmark functions (Sphere, Ackley, Rastrigin, Rosenbrock and Schwefel p2.26). The obtained results are compared with those of standard PSO and different published improved PSO algorithms (SPSO, PSO-XD, CPSO-S and PSO-P5), the comparison showed that TriPSO has the best results.

Keywords

particle swarm optimisation; Ackley benchmark function; Rastrigin benchmark function; Rosenbrock benchmark function; Schwefel benchmark function; Sphere benchmark function; TriPSO algorithm; inertia weight; stagnation problem avoidance; triangular cosine function; triangular functions; triangular particle swarm optimization; triangular sine function; velocity equation; Benchmark testing; Educational institutions; Equations; Mathematical model; Optimization; Particle swarm optimization; Standards; Triangular Particle Swarm Optimization TriPSO;

fLanguage

English

Publisher

ieee

Conference_Titel

Modeling, Simulation and Applied Optimization (ICMSAO), 2013 5th International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-5812-5

Type

conf

DOI

10.1109/ICMSAO.2013.6552560

Filename

6552560