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Proceedings Paper

Uniform design and inertia mutation based particle swarm optimization
Author(s): Boquan Zhang; Yimin Yang; Jianbin Wang
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Paper Abstract

Particle swarm optimization (PSO) is a population-based stochastic optimization technique. It shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). But compared with GA, it has simpler model, fewer parameters, higher intelligence, faster computation, which makes it attractive to some researchers. This paper presents a new particle swarm optimization based on uniform design and inertia mutation (UMPSO). It uses uniform designs (UD) to initialize particles, which makes some particles stay at or near the position where the global optimal solution stays with more probability. So the new PSO can find global optimal solution with more probability and more speed. Particles can keep diverse through mutating inertia particle with the probability of 1 in the process of evolution, which makes the new PSO find more precise solution. The results of simulation verify that the new PSO can find more precise solution with higher speed than the standard one.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 678924 (14 November 2007); doi: 10.1117/12.748515
Show Author Affiliations
Boquan Zhang, Guangdong Univ. of Technology (China)
Yimin Yang, Guangdong Univ. of Technology (China)
Jianbin Wang, Guangdong Univ. of Technology (China)

Published in SPIE Proceedings Vol. 6789:
MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques
Jianguo Liu; Kunio Doi; Patrick S. P. Wang; Qiang Li, Editor(s)

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