Adaptive consensus building in emergency group decision-making with hesitant fuzzy linguistic information: a perspective based on disappointment theory

2020 ◽  
pp. 105971232096920
Author(s):  
Shitao Zhang ◽  
Zhenzhen Ma ◽  
Xiaodi Liu ◽  
Hao Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Consensus Model ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Psychological Behavior ◽  
Disappointment Theory ◽  
Consensus Reaching Process ◽  
Fuzzy Linguistic

In this article, an adaptive consensus model that considers individual disappointment emotion is proposed for emergency multi-attribute group decision-making (MAGDM) problems with hesitant fuzzy linguistic information. Subsequently, it is applied to choose the optimal emergency alternative(s) for the prevention and control of COVID-19 on a college campus. The main innovations and contributions of this article are as follows: (a) Individual modified perceived utility (MPU) based on disappointment theory is integrated into the determination of attribute weights and construction of consensus reaching process (CRP). (b) The MPU-based individual contribution degree and the MPU-based soft group consensus degree are developed. (c) The new emergency CRP mechanism not only considers the rewards and penalties of expert weights but also regards the adaptive updating of attribute weights. Compared with the existing emergency MAGDM models in a hesitant fuzzy linguistic environment, the proposed consensus model has some advantages in improving consensus efficiency and simulating uncertain psychological behavior.

Model for Software Patterns Selection with Fuzzy Linguistic Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7533-7537
Author(s):  
Zhi-Min Li ◽  
Yi-Ding Zhao
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Practical Method ◽  
Harmonic Mean ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Fuzzy Linguistic

With respect to multiple attribute group decision making problem with triangular fuzzy linguistic information, in which the attribute weights and expert weights take the form of real numbers, and the preference values take the form of triangular fuzzy linguistic variables, some operators for aggregating triangular fuzzy linguistic variables, such as the fuzzy linguistic harmonic mean (FLHM) operator, fuzzy linguistic weighted harmonic mean (FLWHM) operator, fuzzy linguistic ordered weighted harmonic mean (FLOWHM) operator, and fuzzy linguistic hybrid harmonic mean (FLHHM) operator are proposed. Based on the FLWHM and FLHHM operators, a practical method is developed for group decision making with triangular fuzzy linguistic variables. Finally, an illustrative example about software patters selection is given to verify the developed approach.

scholarly journals A CONSENSUS MODEL FOR GROUP DECISION MAKING PROBLEMS WITH UNBALANCED FUZZY LINGUISTIC INFORMATION

2009 ◽  
Vol 08 (01) ◽  
pp. 109-131 ◽  
Author(s):  
F. J. CABRERIZO ◽  
S. ALONSO ◽  
E. HERRERA-VIEDMA
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Feedback Mechanism ◽  
Consensus Model ◽  
Linguistic Information ◽  
Linguistic Methodology ◽  
Linguistic Term ◽  
Proximity Measures ◽  
Fuzzy Linguistic

Most group decision making (GDM) problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts' opinions. However, there exist problems whose assessments need to be represented by means of unbalanced linguistic term sets, i.e. using term sets that are not uniformly and symmetrically distributed. The aim of this paper is to present a consensus model for GDM problems with unbalanced fuzzy linguistic information. This consensus model is based on both a fuzzy linguistic methodology to deal with unbalanced linguistic term sets and two consensus criteria, consensus degrees, and proximity measures. To do so, we use a new fuzzy linguistic methodology improving another approach to manage unbalanced fuzzy linguistic information,1 (Int. J. Intell. Syst.22(11) (2007) 1197–1214), which uses the linguistic 2-tuple model as representation base of unbalanced fuzzy linguistic information. In addition, the consensus model presents a feedback mechanism to help experts for reaching the highest degree of consensus possible. There are two main advantages provided by this consensus model. First, its ability to cope with GDM problems with unbalanced fuzzy linguistic information overcoming the problem of finding different discrimination levels in linguistic term sets. Second, it supports the consensus process automatically, avoiding the possible subjectivity that the moderator can introduce in this phase.

Soft consensus measures in group decision making using unbalanced fuzzy linguistic information

2015 ◽  
Vol 21 (11) ◽  
pp. 3037-3050 ◽  
Author(s):  
F. J. Cabrerizo ◽  
R. Al-Hmouz ◽  
A. Morfeq ◽  
A. S. Balamash ◽  
M. A. Martínez ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Linguistic Information ◽  
Fuzzy Linguistic

scholarly journals Fuzzy Linguistic Induced Ordered Weighted Averaging Operator and Its Application

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sidong Xian
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Ordered Weighted Averaging Operator ◽  
Fuzzy Linguistic ◽  
Magdm Problems

With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of fuzzy linguistic scale variables, a decision analysis approach is proposed. In this paper, we develop a new fuzzy linguistic induce OWA (FLIOWA) operator and analyze the properties of it by utilizing some operational laws of fuzzy linguistic scale variables. A method based on the FLIOWA operators for multiple attribute group decision making is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

A Novel Linguistic Group Decision-Making Model Based on Extended Hesitant Fuzzy Linguistic Term Sets

2015 ◽  
Vol 23 (03) ◽  
pp. 379-398 ◽  
Author(s):  
Cuiping Wei ◽  
Na Zhao ◽  
Xijin Tang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Distance Measures ◽  
Linguistic Terms ◽  
Linguistic Information ◽  
Linguistic Group ◽  
Linguistic Term ◽  
Decision Making Model ◽  
Fuzzy Linguistic

Hesitant fuzzy linguistic term set (HFLTS) is a set with ordered consecutive linguistic terms, and is very useful in addressing the situations where people are hesitant in providing their linguistic assessments. Wang [H. Wang, Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making, International Journal of Computational Intelligence Systems 8(1) (2015) 14–33.] removed the consecutive condition to introduce the notion of extended HFLTS (EHFLTS). The generalized form has wider applications in linguistic group decision-making. By introducing distance measures for EHFLTSs, in this paper we develop a novel multi-criteria group decision making model to deal with hesitant fuzzy linguistic information. The model collects group linguistic information by using EHFLTSs and avoids the possible loss of information. Moreover, it can assess the importance weights of criteria according to their subjective and objective information and rank alternatives based on the rationale of TOPSIS. In order to illustrate the applicability of the proposed algorithm, two examples are given and comparisons are made with the other existing methods.

Distance-Based Multi-Criteria Group Decision-Making Approaches with Multi-Hesitant Fuzzy Linguistic Information

2017 ◽  
Vol 16 (04) ◽  
pp. 1069-1099 ◽  
Author(s):  
Jing Wang ◽  
Jian-Qiang Wang ◽  
Hong-Yu Zhang ◽  
Xiao-Hong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Linguistic Distance ◽  
Linguistic Information ◽  
Set Operations ◽  
Linguistic Term ◽  
Linguistic Scale Function ◽  
Fuzzy Linguistic

In this paper, the distance-based multi-criteria group decision-making (MCGDM) approaches using multi-hesitant fuzzy linguistic term sets (MHFLTSs) are proposed. MHFLTSs can contain nonconsecutive and repetitive linguistic terms, so as to deal with repeated linguistic values in group decision-making. A multi-hesitant fuzzy linguistic term element (MHFLTE) can be produced by collecting the evaluation values of several decision-makers or given by one person who has uncertainty in evaluation. The corresponding set operations and comparison rules are defined and the generalized hesitant fuzzy linguistic distance for MHFLTEs is given based on the linguistic scale function. Then this distance is embedded into the TOPSIS, VIKOR and TODIM approaches for the purpose of solving multi-criteria decision-making (MCDM) problems in the context of multi-hesitant fuzzy linguistic information. With increasing concerns about deterioration in environment, organizations are obliged to carry out more environmental sustainable activities than before, such as progressive practices in green supply chain management (GSCM). Therefore, with respect to the application of MHFLTSs in GSCM, two illustrations for evaluating the related alternatives are finally provided, together with the sensitivity and comparison analysis, to show the validity and effectiveness of our proposal.

Approach to Multiple Attribute Group Decision Making Based on Hesitant Fuzzy Linguistic Aggregation Operators

2018 ◽  
Vol 29 (1) ◽  
pp. 423-439 ◽  
Author(s):  
Minghua Shi ◽  
Qingxian Xiao
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
New Approach ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Multiple Attribute ◽  
Fuzzy Linguistic

Abstract Inspired by the nonlinear weighted average operator, this paper proposes several generalized power average operators to aggregate hesitant fuzzy linguistic decision information. It is worth noting that the new operators take both the location and date weight information and the relative closeness of the decision-making information into consideration, a characteristic that results in objectivity and fairness in a group decision making. Moreover, we demonstrate some useful properties of the operators and discuss their associations. A new approach based on the designed operators is then proposed for hesitant fuzzy linguistic multiple attribute group decision-making problems, in which the attribute weights are known or unknown. Finally, this paper demonstrates the efficiency and feasibility of the proposed method through a numerical example.

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