• DocumentCode
    1277488
  • Title

    Solving constraint satisfaction and optimization problems by a neuro-fuzzy approach

  • Author

    Cavalieri, Salvatore ; Russo, Marco

  • Author_Institution
    Ist. di Inf. e Telecommun., Catania Univ., Italy
  • Volume
    29
  • Issue
    6
  • fYear
    1999
  • fDate
    12/1/1999 12:00:00 AM
  • Firstpage
    895
  • Lastpage
    902
  • Abstract
    The solution of constrained satisfaction and constrained optimization problems using a Hopfield model requires determination of the values of a certain number of coefficients linked to the surrounding conditions of the problem. It is quite difficult to determine these values, mainly because a heuristic search is necessary. This is not only time-consuming but may lead to solutions that are far from optimal, or even nonvalid ones. So far, there have been no works in literature offering a general method for the search for coefficents with will guarantee optimal or close to optimal solutions. This paper proposes a fuzzy approach which allows automatic determination of Hopfield coefficients
  • Keywords
    Hopfield neural nets; constraint theory; fuzzy logic; optimisation; Hopfield coefficients; Hopfield model; coefficients; constrained optimization problems; constraint satisfaction problems; heuristic search; neuro-fuzzy approach; Computer science; Constraint optimization; Cost function; Engineering management; Fuzzy logic; Fuzzy sets; Fuzzy systems; Hopfield neural networks; Hybrid intelligent systems; Neural networks;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/3477.809042
  • Filename
    809042