Deviation measures of linguistic preference relations in group decision making

By Zeshui Xu. 2005

733 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/041d85571e7ae51273d4cd6250df6335a6395596

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In Computational Theory and Mathematics

In Management Science and Operations Research

Citations in the corpus

Some Hesitant Fuzzy Aggregation Operators with Their Application in Group Decision Making (2011, methodology): “…several tools have been developed, such as fuzzy set (Zadeh 1965), interval-valued fuzzy set (Zadeh 1975), linguistic fuzzy set (Herrera et al. 1996; Xu 2004, 2005), type-2 fuzzy set (Dubois and Prade 1980; Miyamoto 2005), which allow the degree of an element to a set denoted by the fuzzy number,…”
Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP (2008, background): “Generally, these preference relations can be categorized into multiplicative preference relations [15,19,44], fuzzy preference relations [1,8–10,13,15,24,38,41–47] and linguistic preference relations [17,18,20–23,25,26,48–50,52].”
Consistency-based risk assessment with probabilistic linguistic preference relation (2016, methodology): “To overcome this issue of 1 { | 0,1, , } S s     , Xu [18] extended the additive linguistic evaluation scale and gave a subscript-symmetric linguistic evaluation scale: 2 { | , , 1,0,1, , } S s        , where the mid linguistic label 0 s represents an assessment of “indifference”, and w”
A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust (2018, background): “For instance, Xu [51] proposed a continuous linguistic model as: Let S = {sα |α = −t, .”
Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets (2015, methodology): “A subscript-symmetric additive linguistic term set [32] is shown as: S 1⁄4 fstjt 1⁄4 s; .”
Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making (2013, background): “Several classical extensions of the concept have been developed, including the interval-valued fuzzy set [37,64], intuitionistic fuzzy set [2,3,23,25], intervalvalued intuitionistic fuzzy set [4,22,41], linguistic fuzzy set [46,48], type-2 fuzzy set [5,10,12–14,30,66], type-n fuzzy set [10], and fuz”
Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information (2013, methodology): “Many methods for MADM, such as the TOPSIS method [16] [17] [18], the maximizing deviation method [19] [20] [21], the gray relational analysis method [22], the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method [23] [24] [25], the PROMETHEE (Preference Ranking Organisation METHod…”
On distance and correlation measures of hesitant fuzzy information (2011, background): “On the basis of the Hamming distance, Xu 12 deﬁned the concepts of deviation degrees and similarity degrees between linguistic values, and between linguistic preference relations, respectively.”
Intuitionistic preference relations and their application in group decision making (2007, background): “If sa 2 S, then sa is termed an original linguistic label, otherwise, sa is termed a virtual linguistic label [55].”
A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets (2008, background): “The fuzzy linguistic approach [54]–[56] deals with qualitative aspects that are represented in qualitative terms by means of linguistic variables, providing an important tool for solving problems in different areas such as information retrieval [7], [8], [26]–[28], [35], [36], [57], services evaluat”
Distance and similarity measures for hesitant fuzzy sets (2011, background): “For example, based on the Hamming distance, Xu [38] introduced the concepts of deviation degrees and similarity degrees between two linguistic values, and between two linguistic preference relations, respectively.”
Consistency Measures for Hesitant Fuzzy Linguistic Preference Relations (2014, background): “Xu [24] defined the distance between two linguistic terms, sα and sβ , (sα , sβ ∈ S) as follows:”
Hesitant Fuzzy Linguistic VIKOR Method and Its Application in Qualitative Multiple Criteria Decision Making (2015, background): “To do so, Xu [46] proposed the subscript-symmetric additive linguistic term set, shown as { | , .”
The consensus models with interval preference opinions and their economic interpretation (2015, background): “In many practical instances of decision making, linguistic information [33,34] or fuzzy information [35] are widely used to express DM's preference, which means the crisp value cannot fully denote the real viewpoint of a DM.”