摘要
Particle swarm optimization (PSO) is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PSO is proposed. In θ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. Benchmark testing of nonlinear func- tions is described and the results show that the performance of θ-PSO is much more effective than that of the standard PSO.
Particle swarm optimization （PSO） is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PSO is proposed. In θ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. Benchmark testing of nonlinear functions is described and the results show that the performance of θ-PSO is much more effective than that of the standard PSO.
基金
the National Natural Science Foundation of China (Nos. 60625302 and 60704028)
the Program for ChangjiangScholars and Innovative Research Team in University (No. IRT0721)
the 111 Project (No. B08021)
the Major State Basic Research De-velopment Program of Shanghai (No. 07JC14016)
ShanghaiLeading Academic Discipline Project (No. B504) of China
