A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method

Axioms ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 335
Author(s):  
Parul Thakur ◽  
Bartłomiej Kizielewicz ◽  
Neeraj Gandotra ◽  
Andrii Shekhovtsov ◽  
Namita Saini ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Uncertain Data ◽  
Intuitionistic Fuzzy Set ◽  
Entropy Method ◽  
Entropy Measure ◽  
Intuitionistic Fuzzy ◽  
Entropy Measurement ◽  
Decision Alternative ◽  
Copras Method

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.

Complex intuitionistic fuzzy Maclaurin symmetric mean operators and its application to emergency program selection

2021 ◽  
pp. 1-22
Author(s):  
Riaz Ali ◽  
Saleem Abdullah ◽  
Shakoor Muhammad ◽  
Muhammad Naeem ◽  
Ronnason Chinram
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Score Functions ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Program Selection ◽  
Maclaurin Symmetric Mean ◽  
Complex Intuitionistic Fuzzy Set

Due to the indeterminacy and uncertainty of the decision-makers (DM) in the complex decision making problems of daily life, evaluation and aggregation of the information usually becomes a complicated task. In literature many theories and fuzzy sets (FS) are presented for the evaluation of these decision tasks, but most of these theories and fuzzy sets have failed to explain the uncertainty and vagueness in the decision making issues. Therefore, we use complex intuitionistic fuzzy set (CIFS) instead of fuzzy set and intuitionistic fuzzy set (IFS). A new type of aggregation operation is also developed by the use of complex intuitionistic fuzzy numbers (CIFNs), their accuracy and the score functions are also discussed in detail. Moreover, we utilized the Maclaurin symmetric mean (MSM) operator, which have the ability to capture the relationship among multi-input arguments, as a result, CIF Maclarurin symmetric mean (CIFMSM) operator and CIF dual Maclaurin symmetric mean (CIFDMSM) operator are presented and their characteristics are discussed in detail. On the basis of these operators, a MAGDM method is presented for the solution of group decision making problems. Finally, the validation of the propounded approach is proved by evaluating a numerical example, and by the comparison with the previously researched results.

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.

scholarly journals A COMPLEX PROPORTIONAL ASSESSMENT METHOD FOR GROUP DECISION MAKING IN AN INTERVAL-VALUED INTUITIONISTIC FUZZY ENVIRONMENT

2013 ◽  
Vol 19 (1) ◽  
pp. 22-37 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Shide Sadat Hashemi ◽  
Edmundas Kazimieras Zavadskas
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Assessment Method ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Finite Set ◽  
Copras Method ◽  
Interval Valued

Multi-criteria decision making is an implicational field that concerns with selecting or designing the best scenarios among a finite set of scenarios based on a finite set of criteria. Different methods and techniques for handling this issue have been proposed. Complex proportional assessment is an analytical tool for solving multi-criteria decision making problems. Originally, the COPRAS method has been developed for decision making under a deterministic environment. Since uncertainty is an unavoidable property of decision making due to a lack of knowledge, this paper suggests an extended form of the COPRAS method used for group decision making problems in an uncertain environment where such uncertainty is captured through a generalized form of fuzzy sets - the so called interval valued intuitionistic fuzzy sets. An algorithmic scheme for the COPRAS-IVIF method has been introduced thus examining its application with reference to two numerical examples. It seems that the recommended framework of COPRAS-IVIF can be satisfactorily implemented in decision making problems under ambiguous and ill-defined conditions.

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.

Entropy Analysis on Intuitionistic Fuzzy Sets and Interval-Valued Intuitionistic Fuzzy Sets and its Applications in Mode Assessment on Open Communities

2018 ◽  
Vol 22 (1) ◽  
pp. 147-155 ◽  
Author(s):  
Hang Tian ◽  
Jiaru Li ◽  
Fangwei Zhang ◽  
Yujuan Xu ◽  
Caihong Cui ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Attribute Decision Making ◽  
Intuitionistic Fuzzy Sets ◽  
Entropy Measure ◽  
Generalized Entropy ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Entropy Measures ◽  
Interval Valued

This paper identifies four variables to reveal the internal mechanisms of the entropy measures on intuitionistic fuzzy sets (IFSs) and interval-valued intuitionistic fuzzy sets (IVIFSs). First, four variables are used to propose a pair of generalized entropy measures on IFSs and IVIFSs. Second, three specific entropy measures are put forward to illustrate the effectiveness of the generalized entropy measure functions. Third, a novel multiple attribute decision-making approach under an intuitionistic fuzzy environment is proposed. The superiority of the decision-making approach is that the weight values of the attributes are obtained by their related entropy measures. Finally, the performance of the proposed entropy regulations on IFSs and IVIFSs is illustrated through a mode assessment example on open communities.

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.

Cross-Entropy of Dual Hesitant Fuzzy Sets for Multiple Attribute Decision-Making

2016 ◽  
Vol 8 (3) ◽  
pp. 20-30 ◽  
Author(s):  
Jun Ye
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Attribute Decision Making ◽  
Cross Entropy ◽  
Entropy Measure ◽  
Fuzzy Decision Making ◽  
Hesitant Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
The Cross

This paper proposes a cross-entropy measure between dual hesitant fuzzy sets (DHFSs) as an extension of the cross-entropy measures of intuitionistic fuzzy sets. Then the cross-entropy measure between DHFSs is applied to multiple attribute decision making under dual hesitant fuzzy environments. Through the weighted cross-entropy measure between each alternative and the ideal alternative, we can obtain the ranking order of all alternatives and the best one. The decision-making method based on the cross-entropy measure of DHFSs can deal with dual hesitant fuzzy multiple attribute decision making problems and can automatically take into account much more information than existing hesitant (or intuitionistic) fuzzy decision-making methods and the differences of the evaluation data given by different experts or decision makers. Finally, a practical example about investment alternatives is given to demonstrate the application and effectiveness of the developed approach.

Project investment decision based on VIKOR interval intuitionistic fuzzy set

2021 ◽  
pp. 1-9 ◽  
Author(s):  
Caichuan Wang ◽  
Jiajun Li
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Investment Decision ◽  
Intuitionistic Fuzzy Set ◽  
Reference Value ◽  
Intuitionistic Fuzzy Sets ◽  
Project Investment ◽  
Intuitionistic Fuzzy ◽  
Investment Decision Making ◽  
Decision Making Model

The decision on the investment project is to analyze the feasibility and rationality of the project plan from multiple angles. However, due to the limitations of the actual project investment decision-making, this paper proposes a group decision making method based multifunctional intuitively fuzzy VIKOR interval sets. Firstly, according to the established investment decision-making model, the first round of preliminary candidate project schemes is selected. According to the definition of interval intuitionistic fuzzy sets and the traditional VIKOR method, established the research method of this article, and the project investment decision-making model based on VIKOR interval intuitionistic fuzzy sets is established. Finally, the project schemes are sorted according to the closeness degree of schemes. The results show that when sorting each candidate by Qi value, A4 >  A3 >  A2 >  A1 can be obtained. Because Q4 = 0, Q3 = 0.31, the condition q3-q4 >  0.25 is satisfied. It is concluded that the method can not only meet the needs of actual decision-making, but also has strong operability and practicability. The research results have reference value and guiding significance for project investment decision-making, and can promote the sustainable development of the project.

scholarly journals Intuitionistic Fuzzy Rough TOPSIS Method for Robot Selection using Einstein operators

2021 ◽  
Author(s):  
Abbas Qadir ◽  
Muhammad Naeem ◽  
Saleem Abdullah ◽  
Nejib Ghanmi
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Industrial Robot ◽  
Intuitionistic Fuzzy Set ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Weighted Averaging ◽  
Entropy Measure ◽  
Intuitionistic Fuzzy ◽  
Robot Selection

Abstract Rough set and intuitionistic fuzzy set are very vital role in the decision making method for handling the uncertain and imprecise data of decision makers. The technique for order preference by similarity to ideal solution (TOPSIS) is very attractive method for solving the ranking and multi-criteria decision making (MCDM) problem. The primary goal of this paper is to introduce the Extended TOPSIS for industrial robot selection under intuitionistic fuzzy rough (IFR) information, where the weights of both, decision makers (DMs) and criteria are not-known. First, we develop Intuitionistic fuzzy rough (IFR) aggregation operators based on Einstein T-norm and T-conom, For this firstly we give the idea of intuitionistic fuzzy rough Einstein weighted averaging (IFREWA), intuitionistic fuzzy rough Einstein hybrid averaging (IFREHA) and intuitionistic fuzzy rough ordered weighted averaging (IFREOWA) aggregation operators. The fundamental properties of the proposed operators are described in detail. Furthermore to determine the unknown weights, a generalized distance measure are defined for IFRSs based on intuitionistic fuzzy rough entropy measure. Following that, the intuitionistic fuzzy rough information-based decision-making technique for multi-criteria group decision making (MCGDM) is developed, with all computing steps depicted in simplest form. For considering the conflicting attributes, our proposed model is more accurate and effective. Finally, an example of efficient industrial robot selection is presented to illustrate the feasibility of the proposed intuitionistic fuzzy rough decision support approaches, as well as a discussion of comparative outcomes, demonstrating that the results are feasible and reliable.

An improved fuzzy TODIM method based on entropy measure under Intuitionistic Fuzzy Information

2021 ◽  
Vol 23 (05) ◽  
pp. 464-470
Author(s):  
Sunit Kumar ◽  
◽  
Satish Kumar ◽  
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Score Function ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Fuzzy Information ◽  
Numerical Example ◽  
Intuitionistic Fuzzy ◽  
Todim Method

Intuitionistic fuzzy set (IFS) is one of the most extensive and important tool to accommodate more uncertainties than existing fuzzy set structures. In the present paper, we describe an improved entropy based on TODIM procedure for handling multi-criteria decision-making (MCDM) under IF setting and also the weight information is partially known. First, we study the basic notions and operating laws of IFSs, also the accuracy and score function of it. The new entropy has been proposed. Secondly, the IF information-based decision-making technique for MCDM is presented. Lastly, a numerical example is given related, to demonstrate that their results are credible and feasible.

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