A QPSO algorithm based on hierarchical weight and its application in cloud computing task scheduling

The computing method of the average optimal position is one most important factors that affect optimization performance QPSO algorithm. Therefore, a particle weight based on fitness value grading proposed, which called HWQPSO (hierarchical QPSO). In this method, higher particle, level and greater weight. Particles at different levels have weights, while particles same Through excellent weight, time, absolute few avoided, so algorithm can quickly stably converge to solution, improve ability efficiency order verify effectiveness five standard test functions are selected HWQPSO, QPSO, DWC-QPSO LTQPSO algorithm, algorithms applied task scheduling cloud platform. experiment application comparison, results show solution function faster than other three algorithms. It also find scheme with shortest time consumption balanced resource load in experiment, compared execution maximum was reduced by 35%, 23% 21% respectively.