Abstract
This paper presents an optimization algorithm: particle swarm optimization with expand-and-reduce ability. When particles are trapped into a local optimal solution, a new particle is added and the trapped particle(s) can escape from the trap. The deletion of the particle is also used in order to suppress excessive network grows. The algorithm efficiency is verified through basic numerical experiments. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Miyagawa, E., & Saito, T. (2008). Expand-and-reduce algorithm of particle swarm optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4984 LNCS, pp. 873–881). https://doi.org/10.1007/978-3-540-69158-7_90
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
