• DocumentCode
    3453468
  • Title

    Solving linear Boolean programming problems with imprecise costs

  • Author

    Castro, J.L. ; Herrera, F. ; Verdegay, J.L.

  • Author_Institution
    Dpto. de Ciencias de la Computacion e Inteligencia Artificial, Granada Univ., Spain
  • fYear
    1992
  • fDate
    8-12 Mar 1992
  • Firstpage
    1025
  • Lastpage
    1032
  • Abstract
    The authors present a fuzzy linear Boolean programming problem with fuzzy costs and propose two different approaches for solving the problem. In the case considered, the objective has a fuzzy nature, and, associated to each feasible solution, there is a fuzzy number which is obtained by means of the fuzzy objective function. Hence, to solve the optimization problem, obtaining both the optimal solution and the corresponding fuzzy value of the objective, methods ranking the fuzzy numbers obtained from that function must be considered. The approaches are based on methods for ranking fuzzy numbers, and on the use of the decomposition theorem for fuzzy sets which provides a fuzzy solution to the problem
  • Keywords
    Boolean algebra; fuzzy set theory; linear programming; decomposition theorem; fuzzy costs; fuzzy linear Boolean programming; fuzzy number; fuzzy objective function; fuzzy set theory; optimization; Artificial intelligence; Constraint optimization; Cost function; Costs; Fuzzy sets; Linear programming; Operations research; Optimization methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1992., IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    0-7803-0236-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.1992.258795
  • Filename
    258795