• DocumentCode
    569381
  • Title

    A Study on the Shortest Path Problem Based on Improved Genetic Algorithm

  • Author

    Xu, Zongyan ; Li, Haihua ; Guan, Ye

  • Author_Institution
    Mil. Transp. Dept., Mil. Transp. Univ., Tianjin, China
  • fYear
    2012
  • fDate
    17-19 Aug. 2012
  • Firstpage
    325
  • Lastpage
    328
  • Abstract
    This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.
  • Keywords
    genetic algorithms; network theory (graphs); search problems; crossover strategy; genetic algorithm; intelligent computation; network optimization; optimal selection; optimization ability; search efficiency; shortest path problem; solution quality; Algorithm design and analysis; Biological cells; Genetic algorithms; Optimization; Shortest path problem; Sociology; Statistics; constraints; genetic algorithm; shortest path;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-2406-9
  • Type

    conf

  • DOI
    10.1109/ICCIS.2012.52
  • Filename
    6300502