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
Link To Document :
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