Abstract
Abstract:
In this paper, a new algorithm for particle swarm optimisation (PSO)
is proposed. In this algorithm, the particles are divided into two groups. The
two groups have different focuses when all the particles are searching the
problem space. The first group of particles will search the area around the best
experience of their neighbours. The particles in the second group are influenced
by the best experience of their neighbors and the individual best experience,
which is the same as the standard PSO. Simulation results and comparisons
with the standard PSO 2007 demonstrate that the proposed algorithm
effectively enhances searching efficiency and improves the quality of searching.
Originally presented at Fourth International Conference on Swarm Intelligence (ICSI 2013), Harbin, China, 12-15, June, 2013.