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Intuitionistic fuzzy preference relations
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), 2011We consider properties of intuitionistic fuzzy preference relations. We study preservation of a preference relation by lattice operations, composition and some Atanassov’s operators like F, , P, , Q, , where , 2 [0,1]. We also define semi-properties of intuitionistic fuzzy relations, namely reflexivity, irreflexivity, connectedness, asymmetry ...
Barbara Pekala, Urszula Dudziak
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2014
Fuzzy preference relations (Orlovsky 1978) (also known as reciprocal preference relation (Baets et al. 2006; Xu 2007b,f; Xu and Chen 2008b)) and multiplicative preference relations (Saaty 1980) are the most common tools to express the DMs’ preferences over alternatives in decision making.
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Fuzzy preference relations (Orlovsky 1978) (also known as reciprocal preference relation (Baets et al. 2006; Xu 2007b,f; Xu and Chen 2008b)) and multiplicative preference relations (Saaty 1980) are the most common tools to express the DMs’ preferences over alternatives in decision making.
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Optimization and nontransitive preference-relations
Mathematische Operationsforschung und Statistik. Series Optimization, 1984A good deal of the global theory of optimization can be formulated without the concepts of function and linear space. Even the transitivity of the preference relation is not necessary. In this paper we show that the proofs work also without these concepts and under very weak additional assumptions.
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Intransitive Preference Relations and Preference Differences
1997Aggregation of preference relations by solving a certain optimization problem results in a collective preference which generalizes the majority preference in a natural way (Lemma 2.2). If the optimal preference relation is not required to be necessarily transitive, a cardinal evaluation of the alternatives can be given which allows a one-way cardinal ...
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Mining the Preference Relations and Preference Graphs
2001When knowledge mining starts from contingency tables, many types of knowledge become apparent that would otherwise went unnoticed. In this paper we start from contingency tables for pairs of attributes whose domains are ordered. The domain of each attribute can be interpreted as a preference list.
Jan M. Żytkow, Daniel Arredondo
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Distance based preference relations
2005 International Conference on Machine Learning and Cybernetics, 2005The main contribution of this paper is the definition of a new preference relation, called distance-based preference relation. It allows us to represent the preferential gaps between the alternatives. This makes it possible to express complex preferences that are needed in many realistic settings.
null Zhi-Zheng Zhang +1 more
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Content-Related and Attitude-Related Reasons for Preferences
Royal Institute of Philosophy Supplement, 2006In the first section of this paper I draw, on a purely conceptual level, a distinction between two kinds of reasons: content-related and attitude-related reasons. The established view is that, in the case of the attitude of believing something, there are no attitude-related reasons.
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Intuitionistic Preference Relations
2013The intuitionistic preference relation as a newly developed tool can describe the fuzzy characters of things more detailedly and comprehensively, and is very useful in dealing with vagueness and uncertainty of actual decision making problems. In this chapter, we shall give a systematic introduction to the existing research results on intuitionistic ...
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Intuitionistic Fuzzy Preference Relations
2012In any fuzzy preference relation (FPR), each element denotes the membership degree of how one decision alternative is preferred to another. The values of these elements range between 0 and 1. This key idea originates from Zadeh’s concept of fuzzy sets (Zadeh, 1965).
Zaiwu Gong, Yi Lin, Tianxiang Yao
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Linguistic Preference Relations
2012Preference relations (or called pairwise comparison matrices, judgment matrices) are very useful in expressing decision maker’s preference information over objects by comparing each pair of them in decision making problems of various fields, including politics, social psychology, engineering, management, business and economics, etc.
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