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Spring Tchang

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Proceedings Article | 14 November 2007 Paper

Uniform design and inertia mutation based particle swarm optimization

Boquan Zhang, Yimin Yang, Jianbin Wang

Proceedings Volume 6789, 678924 (2007) https://doi.org/10.1117/12.748515

KEYWORDS: Particles, Particle swarm optimization, Stochastic processes, Genetic algorithms, Standards development, Lithium, Platinum, Roads, Surgery, Chromium

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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.

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