Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Using Sparsification for Parametric Minimum Spanning Tree Problems
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Gradual elements in a fuzzy set
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Gradual Numbers and Their Application to Fuzzy Interval Analysis
IEEE Transactions on Fuzzy Systems
The minimum spanning tree problem with fuzzy costs
Fuzzy Optimization and Decision Making
Characterizations and applications of M-fuzzifying matroids
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper a general approach to combinatorial optimization problems with fuzzy weights is discussed. The results, valid for the interval-valued problems, are extended to the fuzzy-valued ones by exploiting the very recent notion of a gradual number. Some methods for determining the exact degrees of possible and necessary optimality and the possibility distributions of deviations of solutions and elements are proposed. The introduced notions are illustrated by practical examples.