• DocumentCode
    2344462
  • Title

    A New Design of Genetic Algorithm for Solving TSP

  • Author

    Yu, Yingying ; Chen, Yan ; Li, Taoying

  • Author_Institution
    Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China
  • fYear
    2011
  • fDate
    15-19 April 2011
  • Firstpage
    309
  • Lastpage
    313
  • Abstract
    In this paper, we develop an algorithm that is able to quickly obtain an optimal solution to TSP from a huge search space. This algorithm is based upon the use of Genetic Algorithm techniques. The algorithm employs a roulette wheel based selection mechanism, the use of a survival-of-the-fittest strategy, a heuristic crossover operator, and an inversion operator. To illustrate it more clearly, a program based on this algorithm has been implemented, which presents the changing process of the route iteration in a more intuitive way. Finally, we apply it into a TSP problem with fifty cities. By comparing with other published techniques, we can easily know that the proposed algorithm can efficiently complete the search process and derive a better solution.
  • Keywords
    genetic algorithms; search problems; travelling salesman problems; TSP optimal solution; TSP problem; genetic algorithm; heuristic crossover operator; inversion operator; roulette wheel based selection mechanism; route iteration; search process; search space; survival-of-the-fittest strategy; travelling salesman problem; Algorithm design and analysis; Biological cells; Cities and towns; Computers; Encoding; Genetic algorithms; Optimization; GA; TSP; crossover operator; mutation operator; selection operator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
  • Conference_Location
    Yunnan
  • Print_ISBN
    978-1-4244-9712-6
  • Electronic_ISBN
    978-0-7695-4335-2
  • Type

    conf

  • DOI
    10.1109/CSO.2011.46
  • Filename
    5957668