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CHEN Hai-ying, GUO Qiao, XU Li. Grid-Based Pseudo-Parallel Genetic Algorithm and Its Application[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2006, 15(1): 48-52.
Citation: CHEN Hai-ying, GUO Qiao, XU Li. Grid-Based Pseudo-Parallel Genetic Algorithm and Its Application[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2006, 15(1): 48-52.
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Grid-Based Pseudo-Parallel Genetic Algorithm and Its Application

  • 1.

    School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China

  • 2.

    School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China

Funds:theNationalNaturalScienceFundationofChina(60171018)
  • Received Date:2003-12-04
    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.
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    • References (6)
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