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 optimizatio...Show MoreMetadata
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.
Published in: 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)
Date of Conference: 01-06 June 2008
Date Added to IEEE Xplore: 23 September 2008
ISBN Information: