Abstract
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.
Keywords
- Combinatorial Optimization Problem
- Short Path Problem
- Assignment Function
- Possibility Distribution
- Fuzzy Weight
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This work was partially supported by Polish Committee for Scientific Research, grant 3T11C05430.
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Kasperski, A., Zieliński, P. (2007). Using Gradual Numbers for Solving Fuzzy-Valued Combinatorial Optimization Problems. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_65
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DOI: https://doi.org/10.1007/978-3-540-72950-1_65
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