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Grid-Based Pseudo-Parallel Genetic Algorithm and Its Application

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【作者】 陈海英郭巧徐力

【Author】 CHEN Hai-ying1, GUO Qiao2, XU Li2 (1.School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing100081, China; 2.School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China)

【机构】 School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing100081 ChinaSchool of Information Science and Technology Beijing Institute of Technology Beijing100081 China

【Abstract】 Aimed at the problems of premature and lower convergence of simple genetic algorithms (SGA), three ideas——partition the whole search uniformly, multi-genetic operators and multi-populations evolving independently are introduced, and a grid-based pseudo-parallel genetic algorithms (GPPGA) is put forward. Thereafter, the analysis of premature and convergence of GPPGA is made. In the end, GPPGA is tested by both six-peak camel back function, Rosenbrock function and BP network. The result shows the feasibility and effectiveness of GPPGA in overcoming premature and improving convergence speed and accuracy.

【基金】 theNationalNaturalScienceFundationofChina(60171018)
  • 【文献出处】 Journal of Beijing Institute of Technology(English Edition) ,北京理工大学学报(英文版) , 编辑部邮箱 ,2006年01期
  • 【分类号】TP18
  • 【被引频次】2
  • 【下载频次】19
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