A ranking function based on principal-value Pythagorean fuzzy set in multicriteria decision making

2018 ◽  
Vol 33 (8) ◽  
pp. 1717-1730 ◽  
Author(s):  
Sidong Xian ◽  
Yubo Yin ◽  
Mingqiu Fu ◽  
Fengmin Yu
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Ranking Function ◽  
Pythagorean Fuzzy Set ◽  
Multicriteria Decision ◽  
Principal Value

scholarly journals Pythagorean Fuzzy (R,S)-Norm Information Measure for Multicriteria Decision-Making Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Abhishek Guleria ◽  
Rakesh Kumar Bajaj
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Information Measure ◽  
Present Communication ◽  
Pythagorean Fuzzy Set ◽  
Numerical Examples ◽  
Multicriteria Decision ◽  
Decision Making Problem ◽  
Future Work

In the present communication, a parametric (R, S)-norm information measure for the Pythagorean fuzzy set has been proposed with the proof of its validity. The monotonic behavior and maximality feature of the proposed information measure have been studied and presented. Further, an algorithm for solving the multicriteria decision-making problem with the help of the proposed information measure has been provided keeping in view of the different cases for weight criteria, when weights are unknown and other when weights are partially known. Numerical examples for each of the case have been successfully illustrated. Finally, the work has been concluded by providing the scope for future work.

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.

NOVEL ENTROPY MEASURE OF A FUZZY SET AND ITS APPLICATION TO MULTICRITERIA DECISION MAKING WITH FUZZY TOPSIS

2021 ◽  
Vol 16 (7) ◽  
Author(s):  
Manzoor Hussain
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Daily Life ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Vital Role ◽  
Entropy Measure ◽  
Numerical Comparison ◽  
Uncertain Information ◽  
Multicriteria Decision

Fuzzy entropy is being used to measure the uncertainty with high precision and accuracy than classical crisp set theory. It plays a vital role in handling complex daily life problems involving uncertainty. In this manuscript, we first review several existing entropy measures and then propose novel entropy to measure the uncertainty of a fuzzy set. We also construct an axiomatic definition based on the proposed entropy measure. Numerical comparison analysis is carried out with existing entropies to show the reliability and practical applicability of our proposed entropy measure. Numerical results show that our suggested entropy is reasonable and appropriate in dealing with vague and uncertain information. Finally, we utilize our proposed entropy measure to construct fuzzy TOPSIS (Technique for Ordering Preference by Similarity to Ideal Solution) method to manage Multicriteria decision-making problems related to daily life settings. The final results demonstrate the practical effectiveness and applicability of our proposed entropy measure

scholarly journals INTUITIONISTIC FUZZY ENTROPY AND ITS APPLICATIONS TO MULTICRITERIA DECISION MAKING WITH IF-TODIM

2021 ◽  
Vol 16 (7) ◽  
Author(s):  
Sahar Abbas
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Daily Life ◽  
Multicriteria Decision Making ◽  
Fuzzy Entropy ◽  
Numerical Comparison ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Entropy Measures

The intuitionistic fuzzy entropy (IFE) is being used to measure the degree of uncertainty of a fuzzy set (FS) with alarming accuracy and precision more accurately than the fuzzy set theory. Entropy plays a very important role in managing the complex issues efficiently which we often face in our daily life. In this paper, we first review several existing entropy measures of intuitionistic fuzzy sets (IFSs) and then suggest two new entropies of IFSs better than the existing ones. To show the efficiency of proposed entropy measures over existing ones, we conduct a numerical comparison analysis. Our entropy methods are not only showing better performance but also handle those IFSs amicably which the existing method fails to manage. To show the practical applicability and reliability, we utilize our methods to build intuitionistic fuzzy Portuguese of interactive and multicriteria decision making (IF-TODIM) method. The numerical results show that the suggested entropies are convenient and reasonable in handling vague and ambiguous information close to daily life matters.

scholarly journals Linear Diophantine Fuzzy Einstein Aggregation Operators for Multi-Criteria Decision-Making Problems

2021 ◽  
Vol 2021 ◽  
pp. 1-31
Author(s):  
Aiyared Iampan ◽  
Gustavo Santos García ◽  
Muhammad Riaz ◽  
Hafiz Muhammad Athar Farid ◽  
Ronnason Chinram
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Multicriteria Decision Making ◽  
Cerebrovascular Diseases ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Uncertain Information ◽  
Health Administration ◽  
Pythagorean Fuzzy Set

The linear Diophantine fuzzy set (LDFS) has been proved to be an efficient tool in expressing decision maker (DM) evaluation values in multicriteria decision-making (MCDM) procedure. To more effectively represent DMs’ evaluation information in complicated MCDM process, this paper proposes a MCDM method based on proposed novel aggregation operators (AOs) under linear Diophantine fuzzy set (LDFS). A q -Rung orthopair fuzzy set ( q -ROFS), Pythagorean fuzzy set (PFS), and intuitionistic fuzzy set (IFS) are rudimentary concepts in computational intelligence, which have diverse applications in modeling uncertainty and MCDM. Unfortunately, these theories have their own limitations related to the membership and nonmembership grades. The linear Diophantine fuzzy set (LDFS) is a new approach towards uncertainty which has the ability to relax the strict constraints of IFS, PFS, and q –ROFS by considering reference/control parameters. LDFS provides an appropriate way to the decision experts (DEs) in order to deal with vague and uncertain information in a comprehensive way. Under these environments, we introduce several AOs named as linear Diophantine fuzzy Einstein weighted averaging (LDFEWA) operator, linear Diophantine fuzzy Einstein ordered weighted averaging (LDFEOWA) operator, linear Diophantine fuzzy Einstein weighted geometric (LDFEWG) operator, and linear Diophantine fuzzy Einstein ordered weighted geometric (LDFEOWG) operator. We investigate certain characteristics and operational laws with some illustrations. Ultimately, an innovative approach for MCDM under the linear Diophantine fuzzy information is examined by implementing suggested aggregation operators. A useful example related to a country’s national health administration (NHA) to create a fully developed postacute care (PAC) model network for the health recovery of patients suffering from cerebrovascular diseases (CVDs) is exhibited to specify the practicability and efficacy of the intended approach.

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