scholarly journals A Novel Group Decision-Making Approach for Hesitant Fuzzy Linguistic Term Sets and Its Application to VIKOR

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Xiuli Geng ◽  
Yunting Jin ◽  
Yongzheng Zhang
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Group Decision Making ◽  
Rough Set Theory ◽  
Group Decision ◽  
Vikor Method ◽  
Context Free Grammar ◽  
Linguistic Term ◽  
Fuzzy Linguistic ◽  
Context Free

This paper develops a novel group decision-making (GDM) approach for solving multiple-criteria group decision-making (MCGDM) problems with uncertainty. The hesitant fuzzy linguistic term sets (HFLTSs) are applied to elicit the decision makers’ linguistic preferences due to their distinguished efficiency and flexibility in representing uncertainty. However, the existing context-free grammar for linguistic description cannot allow generating the linguistic expressions completely free to limit the richness of HFLTSs, and the related methods for dealing with HFLTSs also have limitations in aggregating HFLTSs with different lengths and types. Therefore, this paper proposes extended context-free grammar and a novel GDM approach for HFLTSs, considering the advantages of the rough set theory and OWA operators. The rough set theory can manage the uncertainty existing in the fuzzy representation and deal with HFLTSs represented by the 2-tuple fuzzy linguistic model to get rough number sets. The OWA operator can aggregate these sets with different numbers of elements into an interval simply and objectively. Then, an extended VIKOR method based on the proposed GDM approach for HFLTSs is presented to solve the MCGDM problems. Finally, two examples are given to illustrate the applicability and validity of the developed GDM approach and the hesitant VIKOR method through sensitivity and comparison analysis with other existing approaches.

Group Decision Making Method Based on Composite Linguistic Expressions

2014 ◽  
Vol 1049-1050 ◽  
pp. 1281-1286
Author(s):  
Wen Zhan Dai ◽  
Yun Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Linguistic Terms ◽  
Traditional Use ◽  
Linguistic Term ◽  
The One ◽  
Decision Making Model ◽  
Fuzzy Linguistic ◽  
Context Free

When decision makers are hesitant among different linguistic terms, the traditional use of one single linguistic term will restrict the accuracy of personal preference expressed by experts, it is necessary to use composite linguistic term which contains both the one single linguistic terms and the comparative linguistic expressions. Firstly, with the use of context-free grammars, two-tuple linguistic representation model and hesitant fuzzy linguistic term sets, the linguistic expressions of the preference relations provided by experts are transformed into judgment matrix, then the suitable aggregation operators will be selected to obtain a best solution to the problem. Finally, a new group decision making model based on composite linguistic expressions has been proposed and a practical example has been analyzed to verify the reasonability and feasibility of the approach.

scholarly journals A BI-OBJECTIVE SCORE-VARIANCE BASED LINEAR ASSIGNMENT METHOD FOR GROUP DECISION MAKING WITH HESITANT FUZZY LINGUISTIC TERM SETS

2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Assignment Method ◽  
Linguistic Term ◽  
Criteria Weights ◽  
Individual Evaluation ◽  
Fuzzy Linguistic ◽  
Linear Assignment

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

A Framework for Multi-Attribute Group Decision-Making Using Double Hierarchy Hesitant Fuzzy Linguistic Term Set

2019 ◽  
Vol 21 (4) ◽  
pp. 1130-1143 ◽  
Author(s):  
R. Krishankumar ◽  
L. S. Subrajaa ◽  
K. S. Ravichandran ◽  
Samarjit Kar ◽  
Arsham Borumand Saeid
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Linguistic Term ◽  
Fuzzy Linguistic

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.

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