scholarly journals Visual information feedback mechanism and attitudinal prioritisation method for group decision making with triangular fuzzy complementary preference relations

2014 ◽  
Vol 279 ◽  
pp. 716-734 ◽  
Author(s):  
Jian Wu ◽  
Francisco Chiclana
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Visual Information ◽  
Group Decision ◽  
Feedback Mechanism ◽  
Information Feedback ◽  
Preference Relations

A CONSENSUS MODEL FOR GROUP DECISION-MAKING PROBLEMS WITH INTERVAL FUZZY PREFERENCE RELATIONS

2012 ◽  
Vol 11 (04) ◽  
pp. 709-725 ◽  
Author(s):  
J. M. TAPIA GARCÍA ◽  
M. J. DEL MORAL ◽  
M. A. MARTÍNEZ ◽  
E. HERRERA-VIEDMA
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Selection Process ◽  
Preference Relation ◽  
Feedback Mechanism ◽  
Consensus Model ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

Interval fuzzy preference relations can be useful to express decision makers' preferences in group decision-making problems. Usually, we apply a selection process and a consensus process to solve a group decision situation. In this paper, we present a consensus model for group decision-making problems with interval fuzzy preference relations. This model is based on two consensus criteria, a consensus measure and a proximity measure, and also on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process. We show an application example in social work.

scholarly journals A MOBILE GROUP DECISION MAKING MODEL FOR HETEROGENEOUS INFORMATION AND CHANGEABLE DECISION CONTEXTS

2011 ◽  
Vol 19 (supp01) ◽  
pp. 33-52 ◽  
Author(s):  
I. J. PEREZ ◽  
F. J. CABRERIZO ◽  
E. HERRERA-VIEDMA
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Decision Process ◽  
Decision Model ◽  
Group Decision ◽  
Feedback Mechanism ◽  
Heterogeneous Information ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Decision Making Model

The aim of this paper is to present a new mobile group decision making model to deal with heterogeneous information and changeable decision contexts. This model takes into account that experts have different backgrounds and knowledge levels, allowing to use different preference representations as fuzzy preference relations or linguistic preference relations with multigranular linguistic information. Furthermore, we allow to introduce some changes on the alternatives of the problem at every stage of the decision process. To do that: i) a mobile implementation is proposed to reduce the number of changes and ii) a mechanism to insert/remove alternatives is included in the model. Finally, our new decision model incorporates a feedback mechanism that sends recommendations to the experts in order to quickly obtain a high consensus level.

scholarly journals A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Meng Zhao ◽  
Ting Liu ◽  
Jia Su ◽  
Meng-Ying Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Preference Relation ◽  
Feedback Mechanism ◽  
Preference Relations ◽  
Linguistic Preference Relation ◽  
Consensus Reaching Process ◽  
Fuzzy Linguistic

In each hesitant fuzzy linguistic preference relation, experts may express their opinions through comparison linguistic information combined with a discrete fuzzy number. In this paper, a hesitant fuzzy linguistic computational model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers is proposed, which enriches the flexibility of group decision-making. First, some main concepts related to discrete fuzzy numbers and an aggregation function of individual subjective linguistic preference relations are introduced. Then, a consistency measure is presented to check and improve the consistency in a given matrix. Further, in order to achieve the predefined degree of consensus and to arrive at the final result, a consensus-reaching process based on the interactive feedback mechanism is defined. Meanwhile, a revised formula is introduced to calculate the consistency and the degree of consensus in a preference relation matrix. Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. The proposed method can address both consistency and consensus, and the results confirmed the effectiveness of the proposed method and its potential use in the qualitative decision-making problems.

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