Abstract
Abstract:
At beginning of the search process of particle swarm
optimization, one of the disadvantages is that PSO focuses on the
global search while the local search is weaken. However, at the
end of the search procedure, the PSO focuses on the local search
as all most all the particles converge to small areas which may
make the particle swarm trapped in the local minima if no
particle find position near the minima at the beginning of search
procedure. To improve the optimization performance, the local
search is necessary for particle swarm optimization. In this paper,
golden ratio is used to determine the size of the search area. Only
two positions need to be checked to find whether there are local
positions with lower fitness value around a certain particle
position. This method is easy to use. It is also tested using several
famous benchmarks with high dimensions and big search space
to the efficiency of the proposed method.