• DocumentCode
    1538400
  • Title

    Nature´s algorithms [genetic algorithms]

  • Author

    Carnahan, Joseph ; Sinha, Roopak

  • Author_Institution
    Naval Surface Warfare Center, Dahlgren, VA, USA
  • Volume
    20
  • Issue
    2
  • fYear
    2001
  • Firstpage
    21
  • Lastpage
    24
  • Abstract
    Combinatorial optimization problems typically require every possible solution to be evaluated to ensure finding the optimal solution. Since such exhaustive searches are often impractical, there is now a vast body of heuristic algorithms for them. Among the algorithms are those based on metaphors borrowed from other areas of science. The idea is that key elements of physical processes can be used abstractly to form the basis of an optimization algorithm. This article presents a broad overview of several metaphor-based algorithms, including the widely-used genetic and simulated annealing algorithms
  • Keywords
    genetic algorithms; simulated annealing; travelling salesman problems; combinatorial optimization problems; genetic algorithms; heuristic algorithms; metaphor-based algorithms; optimal solution; optimization algorithm; physical processes; simulated annealing algorithms; Cities and towns; Cost function; Evolution (biology); Genetic algorithms; Heuristic algorithms; Reliability engineering; Simulated annealing; Traveling salesman problems;
  • fLanguage
    English
  • Journal_Title
    Potentials, IEEE
  • Publisher
    ieee
  • ISSN
    0278-6648
  • Type

    jour

  • DOI
    10.1109/45.954644
  • Filename
    954644