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A Novel Genetic Algorithm with Orthogonal Prediction for Global Numerical Optimization

  • Jun Zhang
  • Jing-Hui Zhong
  • Xiao-Min Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)

Abstract

This paper proposes a novel orthogonal predictive local search (OPLS) to enhance the performance of the conventional genetic algorithms. OPLS operation predicts the most promising direction for the individuals to explore their neighborhood. It uses the orthogonal design method to sample orthogonal combinations to make the prediction. The resulting algorithm is termed the orthogonal predictive genetic algorithm (OPGA). OPGA has been tested on eleven numerical optimization functions in comparison with some typical algorithms. The results demonstrate the effectiveness of the proposed algorithm for achieving better solutions with a faster convergence speed.

Keywords

Genetic algorithm orthogonal design method local search evolutionary algorithm numerical optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jun Zhang
    • 1
  • Jing-Hui Zhong
    • 1
  • Xiao-Min Hu
    • 1
  1. 1.Department of Computer ScienceSUN Yat-sen UniversityGuangzhouChina

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