θ-PSO: a new strategy of particle swarm optimization
Wei-min ZHONG, Shao-jun LI, Feng QIAN
State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China; Automation Institute, East China University of Science and Technology, Shanghai 200237, China
Abstract 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.
