Abstract
In this Chapter, we will illustrate some basic concepts of fuzzy set theory. Given the enormous amount of literature on this field, only the concepts necessary to the understanding of the rest of the book will be presented.
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References
For an extensive discussion on the differences between probability and possibility see Dubois & Prade [1986, 1989].
By compensation in the context of aggregation operators for fuzzy sets is meant the following: “Given that the degree of membership to the aggregated fuzzy set is μAgg (xk) = f(μA(xk), μB(xk)) = k, f is compensatory if μAgg (xk)= k is obtainable for different μA(xk) bv a change in μB(xk) [Zimmermann, 1986, p. 36]”.
The degree of discrimination “refers to the capability of a method to differentiate between alternatives the ratings of which differ only slightly from each other [Zimmermann, 1986]”.
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© 1995 Physica-Verlag Heidelberg
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Munda, G. (1995). Fuzzy Uncertainty in Decision Models. In: Multicriteria Evaluation in a Fuzzy Environment. Contributions to Economics. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-49997-5_5
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DOI: https://doi.org/10.1007/978-3-642-49997-5_5
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0892-6
Online ISBN: 978-3-642-49997-5
eBook Packages: Springer Book Archive