Title :
DNPSO: A Dynamic Niching Particle Swarm Optimizer for multi-modal optimization
Author :
Nickabadi, Ahmad ; Ebadzadeh, Mohammad Mehdi ; Safabakhsh, Reza
Author_Institution :
Amirkabir Univ. of Technol., Tehran
Abstract :
In this paper, a new variant of the PSO algorithm called dynamic niching particle swarm optimizer (DNPSO) is proposed. Similar to basic PSO, DNPSO is a global optimization algorithm in which the main population of the particles is divided into some sub-swarms and a group of free particles. A new sub-swarm forming algorithm is proposed. This new form of sub-swarm creation, combined with free particles which implement a cognition-only model of PSO, brings about a great balance between exploration and exploitation characteristics of the standard PSO. DNPSO is tested with some well-known and widely used benchmark functions and the results are compared with several PSO-based multi-modal optimization methods. The results show that in all cases, DNPSO provides the best solutions.
Keywords :
particle swarm optimisation; dynamic niching particle swarm optimizer; global optimization algorithm; multi-modal optimization; Africa; Evolutionary computation; Particle swarm optimization; DNPSO; PSO; dynamic; multi-modal function optimization niching;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4630771