A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations

By Enrique Herrera-Viedma, Luis Martínez-López, Francisco Mata, Francisco Chiclana. IEEE transactions on fuzzy systems, 2005

648 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/2646b8c5c923241860ff09176c0aac4f3dc66d95

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Citations in the corpus

An Adaptive Consensus Support Model for Group Decision-Making Problems in a Multigranular Fuzzy Linguistic Context (2009, methodology): “In order to evaluate the agreement, it is required to compute similarity measures among the experts [7], [26], [27], [31], [35], [39].”
Consensus reaching in social network group decision making: Research paradigms and challenges (2018, background): “It is often based on two kinds of consensus rules: (a) Identification rule (IR) and direction rule (DR) [44,45].”
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”
Computing the Numerical Scale of the Linguistic Term Set for the 2-Tuple Fuzzy Linguistic Representation Model (2009, background): “It has received increasing attention since its appearance, and been used successfully in a wide range of applications, such as information retrieval [5], [27], [28], [34], and [35], decision-making [2], [6], [7], [11], [14], [15], [17], [30], [33], and [43], consensus process [3], [4], and [29], and”
Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions (2015, background): “90 [12,25], especially in a large-group decision making problem [27,28].”
A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations (2007, methodology): “In fact, as in [16], [21] we compute two different kinds of measures: consensus degrees and proximity measures.”
Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information (2010, methodology): “In fact, as in [25, 29, 34], we compute two different kinds of measures: consensus degrees and proximity measures.”
Computing with words in decision making: foundations, trends and prospects (2009, background): “[51] developed a consensus support system with multigranular linguistic information, Ben-Arieh et al.”
Consistency Measures for Hesitant Fuzzy Linguistic Preference Relations (2014, methodology): “Various preference relations are used to collect preferences in AHP, and numerical preference relations (NPRs) [5]–[7] and linguistic preference relations (LPRs) [8], [9] are the two most common tools according to the element forms in preference relations.”
A review of soft consensus models in a fuzzy environment (2014, methodology): “The automatic consensus models existing in the literature act in a similar way during all consensus rounds although the conditions of GDM problem change [30,48,50,56].”
Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks (2010, methodology): “To solve these problems, the experts are faced by applying two processes before obtaining a final solution [20,28,29]: consensus process and selection process (see Fig.”
A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets (2013, background): “Much research has been developed on GDM problems [18,30,31], being one of the main topics, the managing and modelling of uncertainty by different forms of information, used by experts to provide their preferences, such as utility vectors [5], fuzzy preference relations [21], linguistic variables [14”
A Consensus Model to Detect and Manage Noncooperative Behaviors in Large-Scale Group Decision Making (2014, background): “The commission must achieve a minimum level of agreement of μ = 0.85 before making a decision; the maximum number of rounds of discussion allowed is Maxround = 10, and the acceptability threshold is set as ε = 0.02.”