Title :
A Modified Particle Swarm Optimization Algorithm
Author :
Shuhua, Wen ; Xueliang, Zhang ; Hainan, Li ; Shuyang, Liu ; Jiaying, Wang
Author_Institution :
Taiyuan Univ. of Sci. & Technol.
Abstract :
A modified particle swarm optimization (MPSO) algorithm is presented based on the variance of the population´s fitness. During computing, the inertia weight of MPSO is determined adaptively and randomly according to the variance of the populations fitness. And the ability of , particle swarm optimization algorithm (PSO) to break away from the local optimum is greatly improved. The simulating results show that this algorithm not only has great advantage of convergence property over standard simple PSO, but also can avoid the premature convergence problem effectively
Keywords :
particle swarm optimisation; convergence property; modified particle swarm optimization; populations fitness; Birds; Computational modeling; Convergence; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic mutations; Marine animals; Particle swarm optimization; Particle tracking;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614623