• DocumentCode
    710046
  • Title

    Improved ant colony genetic algorithm hybrid for Sudoku solving

  • Author

    Mantere, Timo

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Vaasa, Vaasa, Finland
  • fYear
    2013
  • fDate
    15-18 Dec. 2013
  • Firstpage
    274
  • Lastpage
    279
  • Abstract
    In this paper we introduce our new improved version of ant colony optimization/genetic algorithm hybrid for Sudoku puzzle solving. Sudoku is combinatorial number puzzle that had become worldwide phenomenon in the last decade. It has also become popular mathematical test problem in order to test new optimization ideas and algorithms for combinatorial problems. In this paper we present our new ideas for populations sorting and elitism rules in order to improve our earlier evolutionary algorithm based Sudoku solvers. Experimental results show that the new ideas significantly improved the speed of Sudoku solving.
  • Keywords
    ant colony optimisation; combinatorial mathematics; games of skill; genetic algorithms; Sudoku solvers; ant colony genetic algorithm hybrid; ant colony optimization; combinatorial number puzzle; elitism rules; evolutionary algorithm; mathematical test problem; populations sorting; Benchmark testing; Cultural differences; Genetic algorithms; Genetics; Heuristic algorithms; Ant colony optimization; Sudoku; combinatorial problems; cultural algorithms; genetic algorithms; puzzle solving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies (WICT), 2013 Third World Congress on
  • Conference_Location
    Hanoi
  • Type

    conf

  • DOI
    10.1109/WICT.2013.7113148
  • Filename
    7113148