Adaptive Function of Genetic Algorithm Optimization and Application

  • Jiang-Bo Huang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 218)


Performance of genetic algorithms is dramatically influenced by algorithmic settings. To improve the research performance of genetic algorithm and avoid its limitation of local optimization, a new adaptive genetic algorithm is applied to optimize three standard benchmark functions selected in this paper. The comparison between the results of the present algorithm and that of the simple genetic algorithm shows that the technique has improved the performance of genetic algorithm.


Genetic algorithm Adaptation Optimization Stereo matching 


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Yangtze Nornal University School of Physics or Electron EngineeringChongqingChina

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