• DocumentCode
    2229002
  • Title

    The improved hybrid genetic algorithm for solving TSP based on Handel-C

  • Author

    Yi, Yang ; Fang, Qian-sheng

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Anhui Univ. of Archit., Hefei, China
  • Volume
    3
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    Traveling Salesman Problem (TSP) is a kind of classical combinatorial optimization problem that is easy to be described but difficult to be solved. It belongs to NP-hard problem and is applied broadly in practice. Thus rapid and effective solving TSP is very important application value in practice. Genetic Algorithm (GA) is a kind of heuristic global optimization search algorithm that simulates the biology evolutionary system. GA is applied quite broadly to the combinatorial optimization domain. The paper adopts Handel-C language to program for the simple and improved hybrid genetic algorithms that solve TSP. The experiment results show that the performance of the improved algorithm enhances greatly.
  • Keywords
    computational complexity; genetic algorithms; programming languages; travelling salesman problems; Handel-C language; biology evolutionary system; combinatorial optimization domain; global optimization search algorithm; improved hybrid genetic algorithm; traveling salesman problem; Genetics; Pediatrics; Genetic Algorithm (GA); Handel-C language; Traveling Salesman Problem (TSP);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5579566
  • Filename
    5579566