scholarly journals Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 735 ◽  
Author(s):  
Arooj Adeel ◽  
Muhammad Akram ◽  
Ali N. A. Koam
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Linguistic Variables ◽  
Topsis Method ◽  
Life Problems ◽  
Electre I ◽  
Linguistic Approach ◽  
Fuzzy Linguistic

The fuzzy linguistic approach provides favorable outputs in several areas, whose description is relatively qualitative. The encouragement for the utilization of sentences or words instead of numbers is that linguistic characterizations or classifications are usually less absolute than algebraic or arithmetical ones. In this research article, we animate the m-polar fuzzy (mF) linguistic approach and elaborate it with real life examples and tabular representation to develop the affluence of linguistic variables based on mF approach. As an extension of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, we develop an m-polar fuzzy linguistic TOPSIS approach for multi-criteria group decision-making (MCGDM). It is used to evaluate the best alternative, to get more authentic and comparable results and to handle the real life problems of having multi-polar information in terms of linguistic variables and values. In this approach decision-makers contribute their estimations in the form of linguistic term sets. To show the efficiency and compatibility of the proposed approach, we compare it with the m-polar fuzzy linguistic ELECTRE-I (Elimination and Choice Translating Reality) approach. Finally, we draw a flow chart of our proposed approach as an algorithm and generate a computer programming code.

scholarly journals Novel m-Polar Fuzzy Linguistic ELECTRE-I Method for Group Decision-Making

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 471 ◽  
Author(s):  
Arooj Adeel ◽  
Muhammad Akram ◽  
Imran Ahmed ◽  
Kashif Nazar
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Linguistic Variables ◽  
Electre I ◽  
Fuzzy Linguistic

Linguistic variables play a vital role in several qualitative decision environments, in which decision-makers assume several feasible linguistic values or criteria instead of a single term for an alternative or variable. The motivation for the use of words or sentences instead of numbers is that linguistic classification and characterizations are generally less precise than numerical ones. In this research article, we encourage the fuzzy linguistic approach and introduce the novel concept known as m-polar fuzzy linguistic variable (mFLV) to increase the affluence of linguistic variables based on m-polar fuzzy (mF) approach. An mF set is an effective concept for interpreting uncertainty and fuzziness. The concept of mFLV is more versatile and sensible for dealing with real-life problems, when data comes from qualitative and multipolar information. We also introduce an mF linguistic ELECTRE-I approach to solve multiple-criteria decision-making (MCDM) and multiple-criteria group decision-making (MCGDM) problems, where the evaluation of the alternatives under suitable linguistic values are determined by the decision-makers. Furthermore, we validate the efficiency of our proposed technique by applying it to real-life examples, such as the salary analysis of companies and by selecting a corrupt country. Finally, we develop an algorithm of our proposed approach, present its flow chart, and generate computer programming code.

Intuitionistic Fuzzy Linguistic Induced Ordered Weighted Averaging Operator for Group Decision Making

2015 ◽  
Vol 23 (04) ◽  
pp. 627-648 ◽  
Author(s):  
Sidong Xian ◽  
Wenting Xue ◽  
Jianfeng Zhang ◽  
Yubo Yin ◽  
Qin Xie
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Linguistic Variables ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Fuzzy Linguistic

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 intuitionistic fuzzy linguistic variables, a decision analysis approach is proposed. In this paper, we develop an intuitionistic fuzzy linguistic induce OWA (IFLIOWA) operator and analyze the properties of it by utilizing some operational laws of intuitionistic fuzzy linguistic variables. A new method based on the IFLIOWA operator for multiple attribute group decision making (MAGDM) is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

scholarly journals Fermatean fuzzy linguistic weighted averaging/geometric operators based on modified operational laws and their application in multiple attribute group decision-making

2021 ◽  
Author(s):  
Rajkumar Verma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Weighted Averaging ◽  
Scale Function ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Linguistic Scale Function ◽  
Fuzzy Linguistic

Fermatean fuzzy linguistic (FFL) set theory provides an efficient tool for modeling a higher level of uncertain and imprecise information, which cannot be represented using intuitionistic fuzzy linguistic (IFL)/Pythagorean fuzzy linguistic (PFL) sets. On the other hand, the linguistic scale function is the better way to consider the semantics of the linguistic terms during the evaluation process. In the present paper, we first define some new modified operational laws for Fermatean fuzzy linguistic numbers (FFLNs) based on linguistic scale function (LSF) to overcome the shortcomings of the existing operational laws and prove some important mathematical properties of them. Based on it, the work defines several new aggregation operators (AOs), namely, the FFL-weighted averaging (FFLWA) operator, the FFL-weighted geometric (FFLWG) operator, the FFL-ordered weighted averaging (FFLOWA) operator, the FFL-ordered weighted geometric (FFLOWG) operator, the FFL-hybrid averaging (FFLHA) operator and the FFL-hybrid geometric (FFLHG) operator under FFL environment. Several properties of these AOs are investigated in detail. Further, based on these operators, a multiple attribute group decision-making (MAGDM) approach with FFL information is developed. Finally, to illustrate the effectiveness of the present approach, a real-life supplier selection problem is presented where the evaluation information of the alternatives is given in terms of FFLNs.

Doubly Extended Fuzzy TOPSIS Method for Group Decision Making

2019 ◽  
Vol 66 (1) ◽  
pp. 27-50
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Final Decision ◽  
Topsis Method ◽  
Decision Matrix

Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.

Models for Multiple Attribute Group Decision Making Based on the Induced Fuzzy Linguistic Ordered Weighted Harmonic Mean Operator and Their Applications

2016 ◽  
Vol 13 (10) ◽  
pp. 7329-7332
Author(s):  
Hao Zhou ◽  
Tao Tao ◽  
Sheng Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Practical Method ◽  
Harmonic Mean ◽  
Security Evaluation ◽  
Linguistic Variables ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Linguistic

In this paper, we investigate the multiple attribute group decision making problem with triangular fuzzy linguistic information. We proposed the induced fuzzy linguistic ordered weighted harmonic mean (IFLOWHM) operator. A practical method based on the FLWHM and IFLOWHM operators is developed for multiple attribute group decision making with triangular fuzzy linguistic variables. Finally, an illustrative example for security evaluation of wireless sensor network is given to verify the developed approach.

scholarly journals A Novel Multicriteria Group Decision-Making Approach with Hesitant Picture Fuzzy Linguistic Information

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Lin Yang ◽  
Xiao-hui Wu ◽  
Jie Qian
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Weighted Average ◽  
Comparison Method ◽  
Operation Rules ◽  
Multicriteria Group Decision Making ◽  
Definition Of ◽  
Fuzzy Linguistic

In real-life group decision-making environment, different decision-makers (DMs) might be hesitant to provide their evaluation by more than two linguistic terms with positive, neutral, negative, and refusal information (e.g., attitude for support, neutral, oppose, and refusal) for criteria of alternative. In order to solve such kinds of decision-making problems, a novel definition of hesitant picture fuzzy linguistic sets (HPFLSs) is introduced, and the HPFLS-based methods are developed. Considering the operation laws appeared in previous papers are not well suitable for HPFLS operation, the novel operation laws of HPFLSs are developed. Then, two aggregation operators of HPFLSs are developed, including hesitant picture fuzzy linguistic weighted average operator (HPFLSWA) and hesitant picture fuzzy linguistic weighted geometric operator (HPFLSGA). Meanwhile, the related proofs are given in detail. Additionally, the comparison method of score and accuracy functions is provided to rank the alternative. Finally, a real-life case of teaching performance evaluation is used to verify the proposed methods. The same case-based comparisons are further conducted between the proposed method and previous methods. The results showed that the proposed method can well overcome the lack of operation rules appeared in previous multicriteria group decision-making (MCGDM) methods and demonstrate effectiveness.

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