Title :
Neighborhood topologies in fully informed and best-of-neighborhood particle swarms
Author :
Kennedy, Jessie ; Mendes, R.
Author_Institution :
U.S. Bur. of Labor Stat., Washington, DC
fDate :
7/1/2006 12:00:00 AM
Abstract :
In this study, we vary the way an individual in the particle swarm interacts with its neighbors. The performance of an individual depends on population topology as well as algorithm version. It appears that a fully informed particle swarm is more susceptible to alterations in the topology, but with a good topology, it can outperform the canonical version
Keywords :
particle swarm optimisation; psychology; social sciences; particle swarm optimization; population topology; social-psychological model; Emulation; Feedforward neural networks; Humans; Informatics; Network topology; Neural networks; Particle swarm optimization; Social network services; Statistics; Testing; Algorithms; optimization; particle swarm;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/TSMCC.2006.875410
