Title :
Study on modified PSO algorithm
Author :
Wang, Dongyun ; Fan, Fulin
Author_Institution :
Dept. of Electr. Eng., Zhongyuan Univ. of Technol., Zhengzhou, China
Abstract :
In order to improve the performance of the Particle Swarm Optimization (PSO) algorithm which weight was decreased linearly, a novel particle swarm optimization (NPSO) algorithm with dynamically changing inertia weight was presented. In each iteration process, the inertia weight of the improved algorithm was changed dynamically based on the current iteration and the best fitness. The new algorithm was tested with three benchmark functions. The experiments show that the disadvantages of slow speed on convergence and easy to be trapped in local optimum of the linearly decreasing weight of the PSO could be overcame by using the proposed PSO.
Keywords :
iterative methods; particle swarm optimisation; inertia weight; iteration process; novel particle swarm optimization; Birds; Convergence; Equations; Heuristic algorithms; IEEE services; Iterative algorithm; Particle swarm optimization; Particle Swarm Optimization; convergence velocity; inertia weight; premature component;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583111