• DocumentCode
    495571
  • Title

    Introducing Gene Clusters into a P2P Based TSP Solving Algorithm

  • Author

    Guangzhi, Ma ; Yansheng, Lu ; Enmin, Song ; Wei, Zhang

  • Author_Institution
    Sch. of Comput., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • Volume
    4
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    795
  • Lastpage
    799
  • Abstract
    The TSP (traveling salesman problem) genetic algorithm is very possible of destroying ever found pieces of a path. To prevent the found pieces from being destroyed, a P2P based TSP genetic algorithm P2PTSPGA which make use of gene clusters is presented. The gene cluster which stands for a series of cities is past down in whole to the offspring from their parent individuals, and is smashed after the first optimum is found to prevent the algorithm from falling into a local optimum. Experiments on CHN144 and instances of TSPLIB show that the optimal solutions are the same as the published results, except the solution 3859 for TSP225 is better than the result 3916 published up-to-date. Our experiments also show that the P2PTSPGA has a high performance in solving such TSPs that number of cities is less than 5000.
  • Keywords
    genetic algorithms; peer-to-peer computing; travelling salesman problems; CHN144; NP-hard problem; P2P based TSP genetic algorithm; P2PTSPGA; TSPLIB; gene clusters; traveling salesman problem; Acceleration; Biological cells; Cities and towns; Clustering algorithms; Computer science; Convergence; Genetic algorithms; Genetic engineering; Genetic mutations; Traveling salesman problems; Gene Cluster; Genetic Algorithm; Peer to Peer; Traveling Salesman Problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.468
  • Filename
    5171105