Title :
The fully informed particle swarm: simpler, maybe better
Author :
Mendes, Rui ; Kennedy, James ; Neves, José
Author_Institution :
Dept.o de Informatica, Univ. do Minho, Braga, Portugal
fDate :
6/1/2004 12:00:00 AM
Abstract :
The canonical particle swarm algorithm is a new approach to optimization, drawing inspiration from group behavior and the establishment of social norms. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to use. However, we feel that each individual is not simply influenced by the best performer among his neighbors. We, thus, decided to make the individuals "fully informed." The results are very promising, as informed individuals seem to find better solutions in all the benchmark functions.
Keywords :
convergence; evolutionary computation; optimisation; convergence; optimization; particle swarm algorithm; social norm establishment; Acceleration; Helium; Iterative algorithms; Particle swarm optimization; Partitioning algorithms; Social network services; Statistics; Optimization; particle swarm optimization; social networks;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/TEVC.2004.826074