Title :
A Particle Swarm Optimization Algorithm with Momentum Factor
Author :
Ren, Jinxia ; Yang, Shuai
Author_Institution :
Sch. of Mech. & Electron. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
Abstract :
The basic particle swarm optimization algorithm updated particles velocity only by the current particles velocity, the personal best position and the excellent particle position. Considering the influence of the previous changes among the current particles velocity, in this paper, the updating formula of particles velocity was mended by appending momentum factor, an improved particle swarm optimization algorithm with momentum factor was proposed. The simulation results show that the improved algorithm has higher accuracy and quicker convergence velocity than the basic particle swarm optimization algorithm.
Keywords :
particle swarm optimisation; excellent particle position; momentum factor; particle swarm optimization algorithm; personal best position; updated particles velocity; Accuracy; Algorithm design and analysis; Companies; Convergence; Educational institutions; Optimization; Particle swarm optimization; Convergence velocity; Momentum factor; Particle Swarm Optimization (PSO);
Conference_Titel :
Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1085-8
DOI :
10.1109/ISCID.2011.13
