Intuitionistic Fuzzy Distance-Based Intuitionistic Fuzzy TOPSIS Method and Application to MADM

2017 ◽  
pp. 72-96
Author(s):  
Jiangxia Nan ◽  
Ting Wang ◽  
Jingjing An
Keyword(s):  
Distance Measure ◽  
Fuzzy Topsis ◽  
Distance Measures ◽  
Ideal Solution ◽  
Intuitionistic Fuzzy Numbers ◽  
Metric Properties ◽  
Fuzzy Distance ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Negative Ideal Solution

In this paper, an intuitionistic fuzzy (IF) distance measure between two triangular intuitionistic fuzzy numbers (TIFNs) is developed. The metric properties of the proposed IF distance measures are also studied. Then, based on the IF distance, an extended TOPSIS is developed to solve multi-attribute decision making (MADM) problems with the ratings of alternatives on attributes of TIFNs. In this methodology, the IF distances between each alternative and the TIFN positive ideal-solution are calculated as well as the TIFN negative ideal-solution. Then the relative closeness degrees obtained of each alternative to the TIFN positive ideal solution are TIFNs. Based on the ranking methods of TIFNs the alternatives are ranked. A numerical example is examined to the validity and practicability of the method proposed in this paper.

Intuitionistic Fuzzy Distance Based TOPSIS Method and Application to MADM

2016 ◽  
Vol 5 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jiangxia Nan ◽  
Ting Wang ◽  
Jingjing An
Keyword(s):  
Distance Measure ◽  
Ideal Solution ◽  
Ranking Methods ◽  
Intuitionistic Fuzzy Numbers ◽  
Metric Properties ◽  
Fuzzy Distance ◽  
Intuitionistic Fuzzy ◽  
Relative Closeness ◽  
Multi Attribute Decision Making ◽  
Negative Ideal Solution

In this paper, an intuitionistic fuzzy (IF) distance measure between two triangular intuitionistic fuzzy numbers (TIFNs) is developed. The metric properties of the proposed IF distance measure are also studied. Then, based on this IF distance, an extended TOPSIS is developed to solve multi-attribute decision making (MADM) problems with the ratings of alternatives on attributes of TIFNs. In this methodology, the IF distances between each alternative and the TIFN positive ideal-solution are calculated as well as the TIFN negative ideal-solution. Then the relative closeness degrees obtained of each alternative to the TIFN positive ideal solution are TIFNs. Based on the ranking methods of TIFNs the alternatives are ranked. A numerical example is examined to the validity and practicability of the method proposed in this paper.

scholarly journals A Theoretical Development of Distance Measure for Intuitionistic Fuzzy Numbers

2010 ◽  
Vol 2010 ◽  
pp. 1-25 ◽  
Author(s):  
Debashree Guha ◽  
Debjani Chakraborty
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Numbers ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Sets ◽  
Distance Measures ◽  
Theoretical Development ◽  
Numerical Examples ◽  
Intuitionistic Fuzzy Numbers ◽  
Metric Properties ◽  
Intuitionistic Fuzzy

The objective of this paper is to introduce a distance measure for intuitionistic fuzzy numbers. Firstly the existing distance measures for intuitionistic fuzzy sets are analyzed and compared with the help of some examples. Then the new distance measure for intuitionistic fuzzy numbers is proposed based on interval difference. Also in particular the type of distance measure for triangle intuitionistic fuzzy numbers is described. The metric properties of the proposed measure are also studied. Some numerical examples are considered for applying the proposed measure and finally the result is compared with the existing ones.

Multi-attribute decision-making method based on a novel distance measure of linguistic intuitionistic fuzzy sets

2021 ◽  
Vol 40 (1) ◽  
pp. 1147-1160
Author(s):  
Yali Cheng ◽  
Yonghong Li ◽  
Jie Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Sets ◽  
Distance Measures ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Linguistic Intuitionistic Fuzzy Sets ◽  
Linguistic Scale Function ◽  
Different Response

Linguistic intuitionistic fuzzy sets can qualitatively rather than quantitatively express data in the form of membership degree. But quantitative tools are required to handle qualitative information. Therefore, an improved linguistic scale function, which can more accurately manifest the subjective feelings of decision-makers, is employed to deal with linguistic intuitionistic information. Subsequently, due to some commonly used distance measures do not comprehensively evaluate the information of linguistic intuitionistic fuzzy sets, an improved distance measure of linguistic intuitionistic fuzzy sets is designed. It considers the cross-evaluation information to get more realistic reasoning results. In addition, a new similarity measure defined by nonlinear Gaussian diffusion model is proposed, which can provide different response scales for different information between various schemes. The properties of these measures are also studied in detail. On this basis, a method in linguistic intuitionistic fuzzy environment is developed to handle multi-attribute decision-making problems. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method and the influence of the parameters is analyzed.

Interval-Valued Intuitionistic Fuzzy Multi-Attribute Decision Making Based on Satisfactory Degree

2017 ◽  
pp. 49-71 ◽  
Author(s):  
Gao-Feng Yu ◽  
Deng-Feng Li ◽  
Jin-Ming Qiu
Keyword(s):  
Nonlinear Programming ◽  
Programming Model ◽  
Intuitionistic Fuzzy Sets ◽  
Ideal Solution ◽  
Satisfactory Degree ◽  
Intuitionistic Fuzzy ◽  
Nonlinear Programming Model ◽  
Multi Attribute Decision Making ◽  
Negative Ideal Solution ◽  
Interval Valued

The aim of this paper is to propose a satisfactory degree method by using nonlinear programming for solving multi-attribute decision making (MADM) problems in which ratings of alternatives on attributes is expressed via interval-valued intuitionistic fuzzy (IVIF) sets and preference information on attributes is incomplete. Concretely, a nonlinear programming model is firstly explored to determine the satisfactory degree which is the ratio of the square of the weight Euclidean distance between an alternative and the IVIF negative ideal solution (IVIFNIS) to the sum of the square of the weight Euclidean distance between the IVIF negative ideal solution (IVIFNIS) and the IVIF positive ideal solution (IVIFPIS). Another nonlinear programming model is also developed to obtain satisfactory intuitionistic fuzzy sets, and then the general satisfactory degrees of the satisfactory intuitionistic fuzzy sets are used to generate the ranking order of the alternatives. Finally, a real example is employed to verify the applicability of the proposed approach and illustrate its practicality and effectiveness.

TOPSIS in Generalized Intuitionistic Fuzzy Environment

2016 ◽  
pp. 630-642 ◽  
Author(s):  
Amal Kumar Adak ◽  
Debashree Manna ◽  
Monoranjan Bhowmik ◽  
Madhumangal Pal
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Data ◽  
Ideal Solution ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
Intuitionistic Fuzzy Data

The aim of this chapter is to investigate the multiple attribute decision making problems to a selected project with generalized intuitionistic fuzzy information in which the information about weights is completely known and the attributes values are taken from the generalized intuitionistic fuzzy environment. Here, we extend the technique for order performance by similarity to ideal solution (TOPSIS) for the generalized intuitionistic fuzzy data. In addition, obtained the concept of possibility degree of generalized intuitionistic fuzzy numbers and used to solve ranking alternative in multi-attribute decision making problems.

A Study and Estimation of Different Distance Measures in Generalized Fuzzy TOPSIS to Improve Ranking Order

2019 ◽  
pp. 207-236
Author(s):  
Martin Aruldoss ◽  
Miranda Lakshmi Travis ◽  
Prasanna Venkatesan Venkatasamy
Keyword(s):  
Fuzzy Topsis ◽  
Distance Measures ◽  
Ideal Solution ◽  
Distance Method ◽  
Distance Methods ◽  
Relative Closeness ◽  
Bit Vector ◽  
Ranking Order ◽  
Negative Ideal Solution ◽  
Target Alternative

Multi criteria decision making (MCDM) is used to solve multiple conflicting criteria. There are different methods available in MCDM out of which TOPSIS is a well- known method to solve precise and imprecise information. In this chapter, triangular fuzzy TOPSIS is considered which has different steps like normalization, weight, finding of positive ideal solution (PIS) and negative ideal solution (NIS), distance between PIS and NIS, calculating relative closeness coefficient (RCC) value and ranking the alternatives. Out of these different steps a distance method is studied. The distance measures are basically used to find the distance between the target alternative and the best and the least alternatives. The most commonly used distance method is Euclidean distance. Many other distance methods are available such as Manhattan, Bit-vector, Hamming, Chebyshev distance, etc. To obtain the appropriate distance, these methods are evaluated. The proposed approach is applied in banking domain to find the suitable user for multi criteria reporting (MCR).

scholarly journals An extension of TOPSIS based on linguistic terms in triangular intuitionistic fuzzy structure

2021 ◽  
pp. 409-424
Author(s):  
Muhammad Saeed ◽  
Asad Mehmood ◽  
Amna Anwar
Keyword(s):  
Euclidean Distance ◽  
Ideal Solution ◽  
Intuitionistic Fuzzy Number ◽  
Linguistic Terms ◽  
Modern Approach ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Triangular Intuitionistic Fuzzy Number ◽  
Negative Ideal Solution ◽  
Fuzzy Framework

Chen [24] introduced the extension of TOPSIS in the fuzzy structure, while this article stretches the modern approach of TOPSIS to the intuitionistic fuzzy framework. Linguistic terms are used in this study to evaluate the weight of each criterion and the rating of alternatives in the context of a triangular intuitionistic fuzzy number. A new intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) are proposed in this model of extended TOPSIS. Euclidean distance is introduced between two triangular intuitionistic fuzzy numbers to calculate separation between each alternative to both (IFPIS) and (IFNIS). The proposed model’s mechanism is presented with the help of an algorithm, and then it is applied to the personal selection problem. Finally, a comparative study is given between this model and other TOPSIS techniques.

scholarly journals Distance-Based Knowledge Measure for Intuitionistic Fuzzy Sets with Its Application in Decision Making

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1119
Author(s):  
Xuan Wu ◽  
Yafei Song ◽  
Yifei Wang
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Malicious Code ◽  
General Level ◽  
Fuzzy Distance ◽  
Intuitionistic Fuzzy ◽  
Knowledge Measure ◽  
Intuitionistic Fuzzy Entropy ◽  
Definition Of

Much attention has been paid to construct an applicable knowledge measure or uncertainty measure for Atanassov’s intuitionistic fuzzy set (AIFS). However, many of these measures were developed from intuitionistic fuzzy entropy, which cannot really reflect the knowledge amount associated with an AIFS well. Some knowledge measures were constructed based on the distinction between an AIFS and its complementary set, which may lead to information loss in decision making. In this paper, knowledge amount of an AIFS is quantified by calculating the distance from an AIFS to the AIFS with maximum uncertainty. Axiomatic properties for the definition of knowledge measure are extended to a more general level. Then the new knowledge measure is developed based on an intuitionistic fuzzy distance measure. The properties of the proposed distance-based knowledge measure are investigated based on mathematical analysis and numerical examples. The proposed knowledge measure is finally applied to solve the multi-attribute group decision-making (MAGDM) problem with intuitionistic fuzzy information. The new MAGDM method is used to evaluate the threat level of malicious code. Experimental results in malicious code threat evaluation demonstrate the effectiveness and validity of proposed method.

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