Dream Effected Particle Swarm Optimization Algorithm
Shengsheng Wang · Journal of Information and Computational Science · 2014
Particle swarm optimization is a stochastic optimization technique based on population. It was gaining popularity during the past decade for the rapid speed of convergence, therefore the researches to improve PSO is increasing. In this paper, we propose a two-phase PSO including day and night phase. In the night phase the particles contort the position information which they gained at day phase, and they will move to the new position in the day phase. The contortion of information is demonstrated effect in Benchmark test function experiments.