• DocumentCode
    1647857
  • Title

    Effectiveness of penalty function in solving the subset sum problem

  • Author

    Wang, Hong ; Ma, Zhiqiang ; Nakayama, Kenji

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Kanazawa Univ., Japan
  • fYear
    1996
  • Firstpage
    422
  • Lastpage
    425
  • Abstract
    We investigate the evolutionary heuristics used as approximation algorithm to the subset sum problem. We propose a graded penalty function in a fitness function of genetic algorithms to penalize an infeasible string in solving the subset sum problem. An exponential term of generation variable, t0, is added into the penalty function for increasing penalty generation by generation. The experiments show that the proposed penalty function is more efficient, than other existing penalty functions. It is suggested that the penalty pressure is increased step by step
  • Keywords
    algorithm theory; combinatorial mathematics; genetic algorithms; heuristic programming; multiprogramming; search problems; storage management; approximation algorithm; evolutionary heuristics; fitness function; generation variable exponential term; genetic algorithms; graded penalty function; infeasible string; penalty function effectiveness; penalty pressure; subset sum problem solving; Constraint optimization; Equations; Genetic algorithms; Space power stations; Springs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
  • Conference_Location
    Nagoya
  • Print_ISBN
    0-7803-2902-3
  • Type

    conf

  • DOI
    10.1109/ICEC.1996.542401
  • Filename
    542401