Title :
A Newly Self-Adaptive Strategy for the PSO
Author :
Xiao, Renyue ; Yu, Jinhai
Author_Institution :
Sch. of Math. Sci., South China Univ. of Technol., Guangzhou
Abstract :
Particle swarm optimization (PSO) is a kind of random optimization algorithm based on the swarm intelligence. It has been used in many optimum problems and Its behave is better. This paper presents newly nonlinear self-adaptive parameters for the PSO (PSO-NL) and we compare it with the linear self-adaptive parameters for the PSO (PSO-TVAC). The experimental results show that the PSO-NL has a fast convergence and is feasible.
Keywords :
particle swarm optimisation; random processes; nonlinear self-adaptive parameter; particle swarm optimization; random optimization algorithm; swarm intelligence; Acceleration; Convergence; Equations; Optimization methods; Particle swarm optimization; Stochastic processes;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.381
