Abstract
For a long time it has been recognized that an exact description of many real life physical situations may be virtually impossible. This is due to the high degree of imprecision involved in real world situations. Zadeh, in his seminal papers [Zadeh, 1965; and 1968], proposed fuzzy set theory as the means for quantifying the inherent fuzziness that is present in ill-posed problems (which by many accounts are the majority of the real life problems in decision making). Fuzziness is a type of imprecision which may be associated with sets in which there is no sharp transition from membership to nonmembership [Bellman and Zadeh, 1970]. Examples of fuzzy sets are classes of objects (entities) characterized by such adjectives as large, small, serious, simple, approximate, etc. [Bellman and Zadeh, 1970].
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© 2000 Springer Science+Business Media Dordrecht
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Triantaphyllou, E. (2000). Fuzzy Sets and Their Operations. In: Multi-criteria Decision Making Methods: A Comparative Study. Applied Optimization, vol 44. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3157-6_12
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DOI: https://doi.org/10.1007/978-1-4757-3157-6_12
Publisher Name: Springer, Boston, MA
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