Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization

This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two principal methods are compared: the recently described Sigma method, and a new “Centroid” method. Drawing on the different dominant behaviors exhibited by the different selection methods, a variety of hybridizations of these is proposed to develop a more robust optimization algorithm. Statistical analysis of the hybrid methods demonstrates their contribution to improved performance of the optimization algorithm.

• Type: Conference
• Year: 2006
• Where: ESCIENCE
• Authors: David Ireland, Andrew Lewis, Sanaz Mostaghim, Junwei Lu
• Keywords: ESCIENCE 2006, Optimization Algorithm, Particle Swarm Optimization, Robust Optimization Algorithm