A Novel Particle Swarm Optimization Based on the Self-Adaptation Strategy of Acceleration Coefficients
Li Guo, Chen Guang Xu · 2009
Based on a new self-adaptation strategy for acceleration coefficients (ACs), a novel particle swarm optimization (PSO) algorithm is presented in this paper. In the newly proposed algorithm, each particle has different ACs which is on-line updated according to its current search state. Numerical experiments on several typical global optimization problems show that the improvements brought about by the algorithm in this paper is greater than that of the canonical PSO (CPSO) in terms of effectiveness.