A fine tuning hybrid particle swarm optimization algorithm
Jun Tang, Xiaojuan Zhao · 2009
Particle swarm optimization (PSO) has shown itsgood performance in many optimization problems. This paper introduces a new approach called hybrid particle swarm optimization like algorithm (HPSO) with fine tuning operators to solve optimisation problems. This method combines the merits of the parameter-free PSO (pf-PSO) and the extrapolated particle swarm optimization like algorithm (ePSO). The performance of all the three PSO algorithms is considerably improved with various fine tuning operators and sometimes more competitive than the recently developed PSO algorithms.