An accelerated approach for solving fuzzy relation equations with a linear objective function

In literature, the optimization model with a linear objective function subject to fuzzy relation equations has been converted into a 0-1 integer programming problem by Fang and Li (1999). They proposed a jump-tracking branch-and-bound method to solve this 0-1 integer programming problem. In this pap...

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Veröffentlicht in:IEEE transactions on fuzzy systems Jg. 10; H. 4; S. 552 - 558
Hauptverfasser: Yan-Kuen Wu, Sy-Ming Guu, Liu, J.Y.-C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2002
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Acceleration
Councils
Equations
Fuzzy
Fuzzy logic
Fuzzy set theory
Industrial relations
Integer programming
Lattices
Linear programming
Mathematical analysis
Mathematical models
Optimization
Optimization methods
Testing
Upper bound
Upper bounds
Vectors
ISSN:1063-6706, 1941-0034
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Zusammenfassung:In literature, the optimization model with a linear objective function subject to fuzzy relation equations has been converted into a 0-1 integer programming problem by Fang and Li (1999). They proposed a jump-tracking branch-and-bound method to solve this 0-1 integer programming problem. In this paper, we propose an upper bound for the optimal objective value. Based on this upper bound and rearranging the structure of the problem, we present a backward jump-tracking branch-and-bound scheme for solving this optimization problem. A numerical example is provided to illustrate our scheme. Furthermore, testing examples show that the performance of our scheme is superior to the procedure in the paper by Fang and Li. Several testing examples show that our initial upper bound is sharp.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2002.800657