Probabilistic hesitant fuzzy set based MCDM method with applications in Portfolio selection process

Abstract Fermatean fuzzy set idea obtained by combining fermatean fuzzy sets and hesitant fuzzy sets can be used in practice to simplify the solution of complicated multi-criteria decision-making (MCDM) problems. Initially, the notion of fermatean hesitant fuzzy set is given and the operations related to this concept are presented. Aggregation operators according to fermatean hesitant fuzzy sets are given and basic properties of these operators are studied. To choose the best alternative in practice, a novel MCDM method that is obtained with operators has been created. Finally, an example of infectious diseases was examined to indicate the effectiveness of the suggested techniques.

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Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making

Complex & Intelligent Systems ◽

10.1007/s40747-021-00446-2 ◽

2021 ◽

Author(s):

Faruk Karaaslan ◽

Mohammed Allaw Dawood Dawood

Keyword(s):

Decision Making ◽

Sensitivity Analysis ◽

Fuzzy Set ◽

Multiple Criteria Decision Making ◽

Aggregation Operators ◽

Multi Criteria Decision Making ◽

Two Dimensional ◽

Weighted Arithmetic ◽

Mcdm Method ◽

Dombi Operations

AbstractComplex fuzzy (CF) sets (CFSs) have a significant role in modelling the problems involving two-dimensional information. Recently, the extensions of CFSs have gained the attention of researchers studying decision-making methods. The complex T-spherical fuzzy set (CTSFS) is an extension of the CFSs introduced in the last times. In this paper, we introduce the Dombi operations on CTSFSs. Based on Dombi operators, we define some aggregation operators, including complex T-spherical Dombi fuzzy weighted arithmetic averaging (CTSDFWAA) operator, complex T-spherical Dombi fuzzy weighted geometric averaging (CTSDFWGA) operator, complex T-spherical Dombi fuzzy ordered weighted arithmetic averaging (CTSDFOWAA) operator, complex T-spherical Dombi fuzzy ordered weighted geometric averaging (CTSDFOWGA) operator, and we obtain some of their properties. In addition, we develop a multi-criteria decision-making (MCDM) method under the CTSF environment and present an algorithm for the proposed method. To show the process of the proposed method, we present an example related to diagnosing the COVID-19. Besides this, we present a sensitivity analysis to reveal the advantages and restrictions of our method.

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QUALIFLEX based ranking system by using Interval Valued Hesitant Fuzzy Set and its application to rank the Diabetic patients

2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) ◽

10.1109/icccis51004.2021.9397179 ◽

2021 ◽

Author(s):

Pankaj Srivastava ◽

Rajkrishna Mondal

Keyword(s):

Fuzzy Set ◽

Hesitant Fuzzy Set ◽

Diabetic Patients ◽

Ranking System ◽

Interval Valued

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Extended TOPSIS method based on the entropy measure and probabilistic hesitant fuzzy information and their application in decision support system

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-202700 ◽

2021 ◽

pp. 1-12

Author(s):

Muhammad Naeem ◽

Muhammad Ali Khan ◽

Saleem Abdullah ◽

Muhammad Qiyas ◽

Saifullah Khan

Keyword(s):

Decision Making ◽

Fuzzy Set ◽

Distance Measure ◽

Group Decision ◽

Hesitant Fuzzy Set ◽

Entropy Measure ◽

Fuzzy Information ◽

Score Functions ◽

Fuzzy Environment ◽

Basic Operating

Probabilistic hesitant fuzzy Set (PHFs) is the most powerful and comprehensive idea to support more complexity than developed fuzzy set (FS) frameworks. In this paper, it can explain a novel, improved TOPSIS-based method for multi-criteria group decision-making (MCGDM) problem through the Probabilistic hesitant fuzzy environment, in which the weights of both experts and criteria are completely unknown. Firstly, we discuss the concept of PHFs, score functions and the basic operating laws of PHFs. In fact, to compute the unknown weight information, the generalized distance measure for PHFs was defined based on the Probabilistic hesitant fuzzy entropy measure. Second, MCGDM will be presented with the PHF information-based decision-making process.

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Interval-Valued Probabilistic Hesitant Fuzzy Set Based Muirhead Mean for Multi-Attribute Group Decision-Making

Mathematics ◽

10.3390/math7040342 ◽

2019 ◽

Vol 7 (4) ◽

pp. 342 ◽

Cited By ~ 6

Author(s):

Krishankumar ◽

Ravichandran ◽

Ahmed ◽

Kar ◽

Peng

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Set ◽

Group Decision ◽

Partial Information ◽

Programming Model ◽

Hesitant Fuzzy Set ◽

Occurrence Probability ◽

Source Selection ◽

Interval Valued

As a powerful generalization to fuzzy set, hesitant fuzzy set (HFS) was introduced, which provided multiple possible membership values to be associated with a specific instance. But HFS did not consider occurrence probability values, and to circumvent the issue, probabilistic HFS (PHFS) was introduced, which associates an occurrence probability value with each hesitant fuzzy element (HFE). Providing such a precise probability value is an open challenge and as a generalization to PHFS, interval-valued PHFS (IVPHFS) was proposed. IVPHFS provided flexibility to decision makers (DMs) by associating a range of values as an occurrence probability for each HFE. To enrich the usefulness of IVPHFS in multi-attribute group decision-making (MAGDM), in this paper, we extend the Muirhead mean (MM) operator to IVPHFS for aggregating preferences. The MM operator is a generalized operator that can effectively capture the interrelationship between multiple attributes. Some properties of the proposed operator are also discussed. Then, a new programming model is proposed for calculating the weights of attributes using DMs’ partial information. Later, a systematic procedure is presented for MAGDM with the proposed operator and the practical use of the operator is demonstrated by using a renewable energy source selection problem. Finally, the strengths and weaknesses of the proposal are discussed in comparison with other methods.

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ERP software selection using intuitionistic fuzzy and interval grey number-based MACBETH method

Grey Systems Theory and Application ◽

10.1108/gs-01-2021-0002 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Mustafa Said Yurtyapan ◽

Erdal Aydemir

Keyword(s):

Decision Making ◽

Fuzzy Set ◽

Selection Process ◽

Intuitionistic Fuzzy Set ◽

Decision Makers ◽

Software Selection ◽

Content Type ◽

Intuitionistic Fuzzy ◽

Expert Opinions ◽

Erp Software

PurposeEnterprise Resource Planning (ERP) software which is a knowledge-based design on the interconnective communication of business units and information share, ensures that business processes such as finance, production, purchasing, sales, logistics and human resources, are integrated and gathered under one roof. This integrated system allows the company to make fast and accurate decisions and increases its competitiveness. Therefore, for an enterprise, choosing the suitable ERP software is extremely important. The aim of this study is to present new research on the ERP software selection process by clarifying the uncertainties and find suitable software in a computational way.Design/methodology/approachERP selection problem design includes uncertainties on the expert opinions and the criteria values using intuitionistic fuzzy set theory and interval grey-numbers to MACBETH multi criteria decision making method. In this paper, a new interval grey MACBETH method approach is proposed, and the degree of greyness approach is used for clarifying the uncertainties. Using this new approach in which grey numbers are used, it is aimed to observe the changes in the importance of the alternatives. Moreover, the intuitionistic fuzzy set method is applied by considering the importance of expert opinions separately.FindingsThe proposed method is based on quantitative decision making derived from qualitative judgments. The results given under uncertain conditions are compared with the results obtained under crisp conditions of the same methods. With the qualitative levels of experts reflected in the decision process, it is clearly seen that ERP software selection problem area has more effective alternative decision solutions to the uncertain environment, and decision makers should not undervalue the unsteadiness of criteria during ERP software selection process.Originality/valueThis study contributes to the relevant literature by (1) utilizing the MACBETH method in the selection of the ERP software by optimization, and (2) validating the importance of expert opinions with uncertainties on a proper ERP software selection procedure. So, the findings of this study can help the decision-makers to evaluate the ERP selection in uncertain conditions.

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A Hesitant Intuitionistic Fuzzy Set Approach to Study Ideals of Semirings

International Journal of Fuzzy System Applications ◽

10.4018/ijfsa.2021070101 ◽

2021 ◽

Vol 10 (3) ◽

pp. 1-17

Author(s):

Debabrata Mandal

Keyword(s):

Set Theory ◽

Fuzzy Set ◽

Cartesian Product ◽

Intuitionistic Fuzzy Set ◽

Ideal Theory ◽

Hesitant Fuzzy Set ◽

Neutrosophic Set ◽

Intuitionistic Fuzzy ◽

Interval Valued ◽

The Ideal

The classical set theory was extended by the theory of fuzzy set and its several generalizations, for example, intuitionistic fuzzy set, interval valued fuzzy set, cubic set, hesitant fuzzy set, soft set, neutrosophic set, etc. In this paper, the author has combined the concepts of intuitionistic fuzzy set and hesitant fuzzy set to study the ideal theory of semirings. After the introduction and the priliminary of the paper, in Section 3, the author has defined hesitant intuitionistic fuzzy ideals and studied several properities of it using the basic operations intersection, homomorphism and cartesian product. In Section 4, the author has also defined hesitant intuitionistic fuzzy bi-ideals and hesitant intuitionistic fuzzy quasi-ideals of a semiring and used these to find some characterizations of regular semiring. In that section, the author also has discussed some inter-relations between hesitant intuitionistic fuzzy ideals, hesitant intuitionistic fuzzy bi-ideals and hesitant intuitionistic fuzzy quasi-ideals, and obtained some of their related properties.

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