scholarly journals Complete Z-intuitionistic Fuzzy MULTIMOORA Method with AHP and its Application to COVID-19

2021 ◽  
Author(s):  
Yijin Zhang ◽  
Jie Huang ◽  
Zongbing Lin
Keyword(s):  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Uncertain Information ◽  
Analytic Hierarchy ◽  
Intuitionistic Fuzzy ◽  
Lack Of Information ◽  
Multicriteria Group Decision Making ◽  
Ranking Aggregation ◽  
Multimoora Method

Abstract For emergencies, the reliability of information can not be guaranteed. At the same time, due to the lack of information and knowledge, neither the criteria itself nor the credibility can be given a precise evaluation by decision-makers(DMs). Therefore, we combine intuitionistic fuzzy set and Z-number to get a new class of fuzzy set, complete Z-intuitionistic fuzzy set(CZIFS), and its degenerate form, A-type Z-intuitionistic fuzzy set(AZIFS) and B-type Z-intuitionistic fuzzy set(BZIFS). CZIFS can serve as a reliable tool to depict the hesitant degree both on the ambiguity and reliability of uncertain information. In addition, we introduce the score and accuracy functions and distance measure of complete Z-intuitionistic fuzzy number(CZIFN), with which we have considered both reliability information and DMs' preference on it. Then, we improve traditional MULTIMOORA by developing reference point(RP) model to consider both the risk and profile of alternatives and integrating analytic hierarchy process(AHP) in the process of ranking aggregation method to take into account the preference of DMs on three subordinate rankings. Besides, to solve multicriteria group decision making(MCGDM) problem, we develop improved MULTIMOORA method to the environment of CZIFN. Finally, to illustrate the proposed method, we give a numerical example, solving site selecting of Fangcang shelter hospital for COVID-19.

A Distance-based Method for Computing Priorities of Intuitionistic Fuzzy Preference Relation and Its Application in AHP

2019 ◽  
Vol 23 (4) ◽  
pp. 329-340
Author(s):  
Akshay Hinduja ◽  
Manju Pandey
Keyword(s):  
Fuzzy Set ◽  
Fuzzy Ahp ◽  
Preference Relation ◽  
Intuitionistic Fuzzy Set ◽  
Analytic Hierarchy ◽  
Intuitionistic Fuzzy ◽  
Course Of Action ◽  
Fuzzy Preference Relations ◽  
Priority Method ◽  
Fuzzy Preference

The notion of multi-criteria decision-making is regarded as the process of finding the best possible alternative or course of action by decision-makers. Often, it entails handling vague, incomplete and inconsistent information. The intuitionistic fuzzy set (IFS) has been proven more effective than a fuzzy set in handling vagueness and uncertainty. The aim of the article is to incorporate the effectiveness of the IFS with the powerfulness of the analytic hierarchy process (AHP) and develop intuitionistic fuzzy AHP (IF-AHP) to cope with the decision problems involving imprecise and hesitant information. In this article, we develop a distance-based novel priority method, which derives unambiguous non-fuzzy priorities of the alternatives from intuitionistic fuzzy preference relations (IFPRs). The proposed priority method is simple in computation yet effective in results. To validate the method, we applied it to the adapted supplier selection problem. This article also presents a comparison of the proposed method with classic and fuzzy AHP using Monte-Carlo simulation approach.

An integrated dynamic intuitionistic fuzzy MADM approach for personnel promotion problem

Kybernetes ◽  
2015 ◽  
Vol 44 (10) ◽  
pp. 1422-1436 ◽  
Author(s):  
Ozkan Bali ◽  
Metin Dagdeviren ◽  
Serkan Gumus
Keyword(s):  
Fuzzy Set ◽  
Success Factors ◽  
Intuitionistic Fuzzy Set ◽  
Senior Managers ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Dynamic Evaluation ◽  
Intuitionistic Fuzzy ◽  
Qualified Personnel ◽  
Fuzzy Madm

Purpose – One of the key success factors for an organization is the promotion of qualified personnel for vacant positions. Especially, the promotion of middle and senior managers play an important role in terms of organization’s success. In personnel promotion problem in which the candidates are nominated within the organization and they have been working for a specific period of time and are known in their organization, the candidates should be evaluated based on their recent as well as past performances to make right selection for the vacant position. For this reason, the purpose of this paper is to propose an integrated dynamic multi-attribute decision-making (MADM) model based on intuitionistic fuzzy set for solving personnel promotion problem. Design/methodology/approach – The proposed model integrates analytic hierarchy process (AHP) technique and the dynamic evaluation by intuitionistic fuzzy operator for personnel promotion. AHP is employed to determine the weight of attributes based on decision maker’s opinions, and the dynamic operator is utilized to aggregate evaluations of candidates for different years. Atanassov’s intuitionistic fuzzy set theory is utilized to represent uncertainty and vagueness in MADM process. Findings – A numerical example is presented to show the applicability of the proposed method for personnel promotion problem and a sensitivity analysis is conducted to demonstrate efficiency of dynamic evaluation. The findings indicate that the varying weights of years employed determined the best candidate for promotion. Originality/value – The novelty of this study is defining personnel promotion as a MADM problem in the literature for the first time and proposing an integrated dynamic intuitionistic fuzzy MADM approach for the solution, in which the candidates are evaluated at different years.

scholarly journals Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Tabasam Rashid ◽  
Shahzad Faizi ◽  
Sohail Zafar
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Fuzzy Entropy ◽  
Entropy Measure ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

Fuzzy entropy means the measurement of fuzziness in a fuzzy set and therefore plays a vital role in solving the fuzzy multicriteria decision making (MCDM) and multicriteria group decision making (MCGDM) problems. In this study, the notion of the measure of distance based entropy for uncertain information in the context of interval-valued intuitionistic fuzzy set (IVIFS) is introduced. The arithmetic and geometric average operators are firstly used to aggregate the interval-valued intuitionistic fuzzy information provided by the decision makers (DMs) or experts corresponding to each alternative, and then the fuzzy entropy of each alternative is calculated based on proposed distance measure. Several numerical examples are solved to demonstrate the application to MCDM and MCGDM problems to show the effectiveness of the proposed approach.

Some Measures of Picture Fuzzy Sets and Their Application

2017 ◽  
Vol 3 (2) ◽  
pp. 35
Author(s):  
Nguyen Van Dinh ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Dissimilarity Measure ◽  
Intuitionistic Fuzzy ◽  
Picture Fuzzy Set ◽  
The Difference ◽  
Picture Fuzzy Sets

To measure the difference of two fuzzy sets (FSs) / intuitionistic sets (IFSs), we can use the distance measure and dissimilarity measure between fuzzy sets/intuitionistic fuzzy set. Characterization of distance/dissimilarity measure between fuzzy sets/intuitionistic fuzzy set is important as it has application in different areas: pattern recognition, image segmentation, and decision making. Picture fuzzy set (PFS) is a generalization of fuzzy set and intuitionistic set, so that it have many application. In this paper, we introduce concepts: difference between PFS-sets, distance measure and dissimilarity measure between picture fuzzy sets, and also provide  the formulas for determining these values. We also present an application of dissimilarity measures in the sample recognition problems, can also be considered a decision-making problem.

scholarly journals New Distance Measure for Atanassov’s Intuitionistic Fuzzy Sets and Its Application in Decision Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 429 ◽  
Author(s):  
Di Ke ◽  
Yafei Song ◽  
Wen Quan
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Research Area ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
The Difference ◽  
Atanassov’S Intuitionistic Fuzzy Sets

The intuitionistic fuzzy set introduced by Atanassov has greater ability in depicting and handling uncertainty. Intuitionistic fuzzy measure is an important research area of intuitionistic fuzzy set theory. Distance measure and similarity measure are two complementary concepts quantifying the difference and closeness of intuitionistic fuzzy sets. This paper addresses the definition of an effective distance measure with concise form and specific meaning for Atanassov’s intuitionistic fuzzy sets (AIFSs). A new distance measure for AIFSs is defined based on a distance measure of interval values and the transformation from AIFSs to interval valued fuzzy sets. The axiomatic properties of the new distance measure are mathematically investigated. Comparative analysis based in numerical examples indicates that the new distance measure is competent to quantify the difference between AIFSs. The application of the new distance measure is also discussed. A new method for multi-attribute decision making (MADM) is developed based on the technique for order preference by similarity to an ideal solution method and the new distance measure. Numerical applications indicate that the developed MADM method can obtain reasonable preference orders. This shows that the new distance measure is effective and rational from both mathematical and practical points of view.

Medical diagnosis using intuitionistic fuzzy set in terms shortest distance measure

2018 ◽  
Vol 11 (3) ◽  
pp. 949 ◽  
Author(s):  
G. Deepa ◽  
B. Praba ◽  
A. Manimaran ◽  
V.M. Chandrasekaran ◽  
K. Rajakumar
Keyword(s):  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Shortest Distance

scholarly journals Fault diagnosis based on TOPSIS method with Manhattan distance

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983327 ◽  
Author(s):  
Wen Jiang ◽  
Meijuan Wang ◽  
Xinyang Deng ◽  
Linfeng Gou
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Weighted Averaging ◽  
Manhattan Distance ◽  
Uncertain Information ◽  
Ideal Solution ◽  
Solution Approach ◽  
Intuitionistic Fuzzy ◽  
Fault Type

Fault diagnosis is important for the maintenance of machinery equipment. Due to the randomness and fuzziness of fault, the relationship between fault types and their characteristics are complicated. Therefore, the determination of fault type is a challenging part of machinery fault diagnosis with the traditional method. To tackle this problem, a fault diagnosis approach based on the technique for order performance by similarity to ideal solution with Manhattan distance is presented in this article. First, the similarity measure between the fault model and the detection sample is constructed based on the Manhattan distance. Then, the similarity is transformed into intuitionistic fuzzy set and the generated intuitionistic fuzzy set is fused by the intuitionistic fuzzy weighted averaging operator. On this basis, the technique for order performance by similarity to the ideal solution approach is utilized to obtain the final rank to ascertain the fault type. The proposed method can handle an intricate relationship between multiple fault types and their various fault characteristics and better express uncertain information. Finally, a fault diagnosis example of the machine rotor and comparative study are conducted to illustrate the application and the effectiveness of the proposed method.

scholarly journals A Comparative Analysis on Geometric Measure in Intuitionistic Fuzzy Set and Interval-Valued Intuitionistic Fuzzy Set

2019 ◽  
pp. 485-491
Author(s):  
A. Manonmani ◽  
M. Suganya
Keyword(s):  
Comparative Analysis ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
Wide Range ◽  
And Algebra ◽  
Interval Valued

Intuitionistic Fuzzy set (IFS) was proposed in early 80’s. It is a well known theory. As a developer in Fuzzy Mathematics, interval – valued Intuitionistic Fuzzy sets (IVIFS) were developed afterwards by Gargo and Atanssov. It has a wide range of applications in the field of Optimization and algebra. There are many distance measure in Fuzzy such as Hamming, Normalized Hamming, Euclidean, Normalized Euclidean, Geometric, Normalized Geometric etc… to calculate the distance between two fuzzy numbers. In this paper, the comparison between Geometric distance measure in Intuitionistic Fuzzy set and interval – valued Intuitionistic Fuzzy sets is explored. The step-wise conservation of Intuitionistic Fuzzy set and interval – valued Intuitionistic Fuzzy sets is also proposed. This type of comparative analysis shows that the distance between Intuitionistic Fuzzy set and interval – valued Intuitionistic Fuzzy sets varies slightly due to boundaries of interval – valued Intuitionistic Fuzzy sets.

An effective similarity/distance measure between intuitionistic fuzzy sets based on the areas of transformed isosceles right triangle and its applications

2021 ◽  
pp. 1-21
Author(s):  
Jinfang Huang ◽  
Xin Jin ◽  
Shin-Jye Lee ◽  
Shanshan Huang ◽  
Qian Jiang
Keyword(s):  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy Sets ◽  
Great Effort ◽  
Intuitionistic Fuzzy ◽  
Measure Model ◽  
And Cluster Analysis ◽  
Mathematical Derivation ◽  
Similarity Distance

Since the intuitionistic fuzzy set (IFS) was proposed by Atanassov, many explorations of this particular fuzzy set were conducted. One of the most important areas is the study of similarity and distance between IFSs, which can measure the degree of deviation of objects with uncertain and vague features, and this technique has great value and potential to solve the fuzzy and uncertain problems in the real world. Based on our previous similarity/distance measure model DJJ (α, β), a new method is proposed for improving the performance of similarity/distance measure model of IFSs, which is derived from the sum of the areas of two triangles constructed by the transformed isosceles triangles of two IFSs. A great effort is made to prove the validity of the proposed method by mathematical derivation. In order to further demonstrate the performance of the proposed method, we apply this method to solve some practical problems such as pattern recognition, medical diagnosis, and cluster analysis. In addition, we also list a series of the existing methods which are used to compare with the proposed method to prove the effectiveness and superiority. The experimental results confirm that the performance of the proposed method exceeds most of the existing methods.

Sign in / Sign up

Export Citation Format

Share Document