scholarly journals A Consensus Model for Extended Comparative Linguistic Expressions with Symbolic Translation

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2198
Author(s):  
Álvaro Labella ◽  
Rosa M. Rodríguez ◽  
Ahmad A. Alzahrani ◽  
Luis Martínez
Keyword(s):  
Group Decision ◽  
Computing With Words ◽  
Fuzzy Information ◽  
Linguistic Terms ◽  
Fuzzy Modelling ◽  
Precise Knowledge ◽  
Consensus Reaching Process ◽  
Linguistic Approach ◽  
Fuzzy Linguistic ◽  
Computational Processes

Consensus Reaching Process (CRP) is a necessary process to achieve agreed solutions in group decision making (GDM) problems. Usually, these problems are defined in uncertain contexts, in which experts do not have a full and precise knowledge about all aspects of the problem. In real-world GDM problems under uncertainty, it is usual that experts express their preferences by using linguistic expressions. Consequently, different methodologies have modelled linguistic information, in which computing with words stands out and whose basis is the fuzzy linguistic approach and their extensions. Even though, multiple consensus approaches under fuzzy linguistic environments have been proposed in the specialized literature, there are still some areas where their performance must be improved because of several persistent drawbacks. The drawbacks include the use of single linguistic terms that are not always enough to model the uncertainty in experts’ knowledge or the oversimplification of fuzzy information during the computational processes by defuzzification processes into crisp values, which usually implies a loss of information and precision in the results and also a lack of interpretability. Therefore, to improving the effects of previous drawbacks, this paper aims at presenting a novel CRP for GDM problems dealing with Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) for modelling experts’ linguistic preferences. Such a CRP will overcome previous limitations because ELICIT information allows both fuzzy modelling of the experts’ uncertainty including hesitancy and performs comprehensive fuzzy computations to, ultimately, obtain precise and understandable linguistic results. Additionally, the proposed CRP model is implemented and integrated into the CRP support system so-called A FRamework for the analYsis of Consensus Approaches (AFRYCA) 3.0 that facilitates the application of the proposed CRP and its comparison with previous models.

THE 2-TUPLE LINGUISTIC COMPUTATIONAL MODEL: ADVANTAGES OF ITS LINGUISTIC DESCRIPTION, ACCURACY AND CONSISTENCY

2001 ◽  
Vol 09 (supp01) ◽  
pp. 33-48 ◽  
Author(s):  
F. HERRERA ◽  
L. MARTINEZ
Keyword(s):  
Computational Model ◽  
Multicriteria Decision Making ◽  
Extension Principle ◽  
Computing With Words ◽  
Linguistic Context ◽  
Linguistic Description ◽  
Decision Making Problem ◽  
Linguistic Approach ◽  
Fuzzy Linguistic ◽  
Computational Processes

The Fuzzy Linguistic Approach has been applied successfully to different areas. The use of linguistic information for modelling expert preferences implies the use of processes of Computing with Words. To accomplish these processes different approaches has been proposed in the literature: (i) Computational model based on the Extension Principle, (ii) the symbolic one(also called ordinal approach), and (iii) the 2-tuple linguistic computational model. The main problem of the classical approaches, (i) and (ii), is the loss of information and lack of precision during the computational processes. In this paper, we want to compare the linguistic description, accuracy and consistency of the results obtained using each model over the rest ones. To do so, we shall solve a Multiexpert Multicriteria Decision-Making problem defined in a multigranularity linguistic context using the different computational approaches. This comparison helps us to decide what model is more adequated for computing with words.

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.

scholarly journals An overview of intuitionistic linguistic fuzzy information aggregations and applications

2018 ◽  
Vol 1 (1) ◽  
pp. 55-78
Author(s):  
Peide Liu ◽  
Hui Gao
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Group Decision ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Future Research ◽  
Linguistic Variables ◽  
Fuzzy Information ◽  
Linguistic Terms ◽  
Content Type

Purpose Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI. Design/methodology/approach First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs. Findings IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs. Originality/value The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

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 Probabilistic Hesitant Intuitionistic Fuzzy Linguistic Term Sets and Their Application in Multiple Attribute Group Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1932
Author(s):  
You Peng ◽  
Yifang Tao ◽  
Boyi Wu ◽  
Xiaoxin Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Technology Selection ◽  
Linguistic Terms ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Linguistic Term ◽  
Correlation Measures ◽  
Fuzzy Linguistic

Multi-attribute group decision-making (MAGDM) is widely applied to various areas for solving real-life problems, including technology selection, credit assessment, strategic planning evaluation, supplier selection, etc. To describe the complex and imprecise cognition, it is more convenient to provide the decision-making information in linguistic terms rather than concrete numerical values. Thus, several linguistic models, such as the fuzzy linguistic approach (FLA), hesitant fuzzy linguistic term sets (HFLTSs), hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs), and probabilistic linguistic term sets (PLTS) have been proposed successively. Due to the flexibility and comprehensiveness of PLTS, it has aroused growing concern. However, it also has a big limitation of requiring the membership degree to be 1 by default, and it does not consider the degree of non-membership and hesitancy of a linguistic variable. Therefore, the probabilistic hesitant intuitionistic fuzzy linguistic term sets (PHIFLTSs) have been presented to extend the PLTS by combining the membership and non-membership in symmetry to depict the evaluation of the experts. To overcome the existing shortcomings and enrich the methodology framework of PHIFLTSs, some novel operational laws are defined to extend the applicability and methodology of the PHIFLTSs in MAGDM. Furthermore, the distance and correlation measures for the PHIFLTSs are improved to make up the shortage of the current distance measures. In addition, the unbalanced linguistic terms are taken into account to represent the cognitive complex information of experts. At last, a MAGDM model based on the multiplicative multi-objective optimization by ratio analysis (MULTIMOORA) approach with the use of the developed novel operational laws and correlation measures is presented, which results in more accuracy and effectiveness. A real-word application example is presented to demonstrate the working of the proposed methodology. Moreover, a thorough comparison is done with related existing works in order to show the validity of this methodology.

scholarly journals An Interactive Consensus Model for Group Decision-Making with Incomplete Multi-Granular 2-Tuple Fuzzy Linguistic Preference Relations

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yongming Song ◽  
Feng Yuan
Keyword(s):  
Decision Making ◽  
Mathematical Programming ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Dynamic Adjustment ◽  
Emergency Plan ◽  
Preference Relations ◽  
Consensus Reaching Process ◽  
Fuzzy Linguistic

As a result of the heterogeneity of decision-makers, it is more suitable to use multi-granular linguistic information to express assessing information over alternatives for decision-makers. Decision-makers may only provide partial preference information as the limitation of knowledge over the alternatives. Thus, the incomplete multi-granular 2-tuple fuzzy linguistic preference relations (IMGFLPRs) can be applied to manage the GDM problems in complex environments. In this paper, we propose a novel group decision-making (GDM) model based on mathematical programming with IMGFLPRs. It is more important that the proposed mathematical programming can directly deal with IMGFLPRs and does not need to be converted into a uniform form. By this means, we construct a consensus reaching process based on IMGFLPRs, considering simultaneously dynamic adjustment of experts’ weight. Finally, an emergency plan selection problem is solved by the proposed model, which shows the result of GDM is effectiveness.

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