Evaluation of Comprehensive Learning Particle Swarm Optimizer

Abstract. Particle Swarm Optimizer (PSO) is one of the evolutionary computation techniques based on swarm intelligence. Comprehensive Learning Particle Swarm Optimizer (CLPSO) is a variant of the original Particle Swarm Optimizer which uses a new learning strategy to make the particles have different learning exemplars for different dimensions. This paper investigates the effects of learning proportion Pc in the CLPSO, showing that different Pc realizes different performance on different problems.

• Type: Conference
• Year: 2004
• Where: ICONIP
• Authors: Jing J. Liang, A. Kai Qin, Ponnuthurai N. Suganthan, S. Baskar
• Keywords: Comprehensive Learning Particle, ICONIP 2004, ICONIP 2007, Particle Swarm Optimizer, Swarm Intelligence