Title :
PSO with sharing for multimodal function optimization
Author :
Li, Tao ; Wei, Chengjian ; Pei, Wenjang
Author_Institution :
Coll. of Inf. Sci. & Eng., Nanjing Univ. of Technol., China
Abstract :
The particle swarm optimizer (PSO) has exhibited good performance on unimodal problem. But on multimodal problem it tends to suffer from premature convergence. In this paper, we propose a modification of the base PSO named fitness sharing particle swarm optimizer (FSPSO) to solve such problem. Through using fitness sharing technique, FSPSO can maintain diversity and avoid convergence to local solution successfully. Experiment indicates that FSPSO is an effective strategy on multimodal problem.
Keywords :
convergence; modal analysis; optimisation; fitness sharing particle swarm optimizer; multimodal function optimization; particle swarm optimizer; premature convergence; Acceleration; Birds; Ecosystems; Equations; Genetic algorithms; History; Information science; Multidimensional systems; Particle swarm optimization; Topology;
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
DOI :
10.1109/ICNNSP.2003.1279305