Title :
A Novel Swarm Intelligence Optimization Based on Gene Mutation
Author_Institution :
Sch. of Inf., Henan Univ. of Finance & Econ., Zhengzhou, China
Abstract :
Particle swarm optimization (PSO) is one of important swarm intelligence (SI) methods. So far, more and more results of PSO application have been published by researchers. The premature convergence and lower local search performance are drawbacks of PSO. This paper proposes a novel gene mutation PSO (GMPSO), mutates some components of particles by the probability, makes a lot of experiments. The results of the research and the experiments indicate that the method can obviously improve the performance of PSO, is credible in theory and is feasible in technique.
Keywords :
particle swarm optimisation; probability; gene mutation PSO; lower local search performance; particle swarm optimization; probability; swarm intelligence method; Ant colony optimization; Convergence; Finance; Genetic mutations; Intelligent systems; Optimization methods; Particle swarm optimization; Particle tracking; Power generation economics; Space technology;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.27