Normalized population diversity in particle swarm optimization

Authors:
Shi Cheng;Yuhui Shi
Affiliations:
Dept. of Electrical Engineering and Electronics, University of Liverpool, Liverpool, UK and Dept. of Electrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China;Dept. of Electrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China
Venue:
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Year:
2011

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Abstract

Particle swarm optimization (PSO) algorithm can be viewed as a series of iterative matrix computation and its population diversity can be considered as an observation of the distribution of matrix elements. In this paper, PSO algorithm is first represented in the matrix format, then the PSO normalized population diversities are defined and discussed based on matrix analysis. Based on the analysis of the relationship between pairs of vectors in PSO solution matrix, different population diversities are defined for separable and non-separable problems, respectively. Experiments on benchmark functions are conducted and simulation results illustrate the effectiveness and usefulness of the proposed normalized population diversities.