Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization
Abstract
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.
Conference Title
e-Science 2006, Second IEEE International Conference on e-Science and Grid Computing
Copyright Statement
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