Fermatean fuzzy TOPSIS method with Dombi aggregation operators and its application in multi-criteria decision making

2020 ◽  
Vol 39 (1) ◽  
pp. 851-869
Author(s):  
Salih Berkan Aydemir ◽  
Sevcan Yilmaz Gunduz
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Topsis Method

scholarly journals Decision-Making Analysis Based on Fermatean Fuzzy Yager Aggregation Operators with Application in COVID-19 Testing Facility

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Harish Garg ◽  
Gulfam Shahzadi ◽  
Muhammad Akram
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Weighted Average ◽  
Fuzzy Topsis ◽  
Aggregation Operators ◽  
Topsis Method ◽  
Research Article ◽  
Testing Facility ◽  
Ordered Weighted Average ◽  
Excellent Tool

This research article is devoted to establish some general aggregation operators, based on Yager’s t-norm and t-conorm, to cumulate the Fermatean fuzzy data in decision-making environments. The Fermatean fuzzy sets (FFSs), an extension of the orthopair fuzzy sets, are characterized by both membership degree (MD) and nonmembership degree (NMD) that enable them to serve as an excellent tool to represent inexact human opinions in the decision-making process. In this article, the valuable properties of the FFS are merged with the Yager operator to propose six new operators, namely, Fermatean fuzzy Yager weighted average (FFYWA), Fermatean fuzzy Yager ordered weighted average (FFYOWA), Fermatean fuzzy Yager hybrid weighted average (FFYHWA), Fermatean fuzzy Yager weighted geometric (FFYWG), Fermatean fuzzy Yager ordered weighted geometric (FFYOWG), and Fermatean fuzzy Yager hybrid weighted geometric (FFYHWG) operators. A comprehensive discussion is made to elaborate the dominant properties of the proposed operators. To verify the importance of the proposed operators, an MADM strategy is presented along with an application for selecting an authentic lab for the COVID-19 test. The superiorities of the proposed operators and limitations of the existing operators are discussed with the help of a comparative study. Moreover, we have explained comparison between the proposed theory and the Fermatean fuzzy TOPSIS method to check the accuracy and validity of the proposed operators. The influence of various values of the parameter in the Yager operator on decision-making results is also examined.

New type of cancer patients based on triangular cubic hesitant fuzzy TOPSIS method

2019 ◽  
Vol 13 (01) ◽  
pp. 2050002
Author(s):  
Aliya Fahmi ◽  
Muhammad Aslam ◽  
Fuad Ali Ahmed Almahdi ◽  
Fazli Amin
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Hamming Distance ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Operational Laws ◽  
New Type ◽  
Mcdm Method

In this paper, we define the new idea of triangular cubic hesitant fuzzy number (TCHFN). We discuss some basic operational laws of triangular cubic hesitant fuzzy number and hamming distance of TCHFNs. We introduce the new concept of triangular cubic hesitant TOPSIS method. Furthermore, we extend the classical cubic hesitant the technique for order of preference by similarity to ideal solution (TOPSIS) method to solve the Multi-Criteria decision-making (MCDM) method based on triangular cubic hesitant TOPSIS method. The new ranking method for TCHFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.

Some Score Functions on Fermatean Fuzzy Sets and Its Application to Bride Selection Based on TOPSIS Method

2021 ◽  
Vol 10 (3) ◽  
pp. 18-29
Author(s):  
Laxminarayan Sahoo
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Score Function ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Topsis Method ◽  
Score Functions ◽  
Relative Closeness ◽  
Separation Measure

The aim of this paper is to propose some score functions for the fruitful ranking of fermatean fuzzy sets (FFSs) and fermatean fuzzy TOPSIS method based on proposed score functions. fermatean fuzzy sets proposed by Senapati and Yager can handle uncertain information more easily in the process of multi-criteria decision making (MCDM). In this paper, the authors have proposed three newly improved score functions for effective ranking of fermatean fuzzy sets. Here, they have applied the proposed score function to calculate the separation measure of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficient. Based on different types of score functions, they have employed the TOPSIS method to solve the multi-criteria decision-making (MCDM) problem in which all preference information provided by the decision makers is expressed in terms of fermatean fuzzy decision matrices. Finally, a numerical example for selecting the bride form matrimonial site has been considered to illustrate the proposed method.

The Technique for Order of Preference by Similarity to Ideal Solution Method in Fuzzy Environment

2020 ◽  
pp. 139-168
Author(s):  
Merve Cengiz Toklu
Keyword(s):  
Decision Making ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Order Preference ◽  
Fuzzy Logic Approach

Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.

scholarly journals Trapezoidal Linguistic Cubic Fuzzy TOPSIS Method and Application in a Group Decision Making Program

2019 ◽  
Vol 29 (1) ◽  
pp. 1283-1300 ◽  
Author(s):  
Aliya Fahmi ◽  
Saleem Abdullah ◽  
Fazli Amin ◽  
Muhammad Aslam ◽  
Shah Hussain
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Hamming Distance ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Mcdm Method

Abstract The aim of this paper is to define some new operation laws for the trapezoidal linguistic cubic fuzzy number and Hamming distance. Furthermore, we define and use the trapezoidal linguistic cubic fuzzy TOPSIS method to solve the multi criteria decision making (MCDM) method. The new ranking method for trapezoidal linguistic cubic fuzzy numbers (TrLCFNs) are used to rank the alternatives. Finally, an illustrative example is given to verify and prove the practicality and effectiveness of the proposed method.

scholarly journals APPLICATION OF TOPSIS METHOD WITH TRAPEZOIDAL FUZZY NUMBERS

2021 ◽  
Author(s):  
Salimov Vagif Hasan Oglu
Keyword(s):  
Decision Making ◽  
Test Problem ◽  
Fuzzy Numbers ◽  
Fuzzy Topsis ◽  
Practical Implementation ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Solution Approach ◽  
Application Problem

The article is devoted to the problem of multi-criteria decision making. As application problem is used the equipment selection problem. The analysis of existing methods for solving this problem is given. As a method for solving this problem fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is proposed. This method is based on ideal solution approach. The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented.

scholarly journals Evaluating Olympic Pictograms Using Fuzzy TOPSIS – Focus on Judo, Taekwondo, Boxing, and Wrestling

2021 ◽  
Author(s):  
Choi kyoungho ◽  
Kim Bongseok ◽  
Jinhee Choi
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Weight Changes ◽  
Beijing Olympics ◽  
Priority Ranking ◽  
The Ideal

This study evaluated the ranking of comprehensibility of the pictograms for judo, taekwondo, boxing, and wrestling used in the six games from the 27th Sydney Olympics in 2000 to the 32nd Tokyo Olympics in 2021. The evaluation was done using the Fuzzy TOPSIS method, one of the multi-criteria decision-making methodologies commonly used in economics and others fields. The results are as follows. The first, pictograms from the 2008 Beijing Olympics ranked first in three sports: taekwondo, boxing, and wrestling, but there were no pictograms that consistently ranked first or sixth in all sports. Second, the result of the sensitivity analysis shows a possibility that the ranking will be reversed if the weight of the evaluation factors changes, but in the 1000-time repetitive prediction, the better the evaluation ranking, the closer the value of the priority ranking to the ideal solution on average even if the weight changes.

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