Uniform design and inertia mutation based particle swarm optimization

Boquan Zhang; Yimin Yang; Jianbin Wang

doi:10.1117/12.748515

14 November 2007 Uniform design and inertia mutation based particle swarm optimization

Boquan Zhang, Yimin Yang, Jianbin Wang

Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 678924 (2007) https://doi.org/10.1117/12.748515
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Boquan Zhang, Yimin Yang, and Jianbin Wang "Uniform design and inertia mutation based particle swarm optimization", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 678924 (14 November 2007); https://doi.org/10.1117/12.748515

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