scholarly journals A New Approach to Fuzzy TOPSIS Method Based on Entropy Measure under Spherical Fuzzy Information

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1231 ◽  
Author(s):  
Omar Barukab ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Muhammad Arif ◽  
Sher Afzal Khan
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Entropy Measure ◽  
Fuzzy Decision ◽  
Fuzzy Information ◽  
Comparative Results ◽  
Robot Selection

Spherical fuzzy set (SFS) is one of the most important and extensive concept to accommodate more uncertainties than existing fuzzy set structures. In this article, we will describe a novel enhanced TOPSIS-based procedure for tackling multi attribute group decision making (MAGDM) issues under spherical fuzzy setting, in which the weights of both decision-makers (DMs) and criteria are totally unknown. First, we study the notion of SFSs, the score and accuracy functions of SFSs and their basic operating laws. In addition, defined the generalized distance measure for SFSs based on spherical fuzzy entropy measure to compute the unknown weights information. Secondly, the spherical fuzzy information-based decision-making technique for MAGDM is presented. Lastly, an illustrative example is delivered with robot selection to reveal the efficiency of the proposed spherical fuzzy decision support approach, along with the discussion of comparative results, to prove that their results are feasible and credible.

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

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.

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.

Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA)

2005 ◽  
Vol 13 (1) ◽  
pp. 23-56 ◽  
Author(s):  
Badredine Arfi
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Trust And Power

In this article I use linguistic fuzzy-set theory to analyze the process of decision making in politics. I first introduce a number of relevant elements of (numerical and linguistic) fuzzy-set theory that are needed to understand the terminology as well as to grasp the scope and depth of the approach. I then explicate a linguistic fuzzy-set approach (LFSA) to the process of decision making under conditions in which the decision makers are required to simultaneously satisfy multiple criteria. The LFSA approach is illustrated through a running (hypothetical) example of a situation in which state leaders need to decide how to combine trust and power to make a choice on security alignment.

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

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.

Prioritized weighted aggregation operators under complex pythagorean fuzzy information

2020 ◽  
Vol 39 (3) ◽  
pp. 4763-4783
Author(s):  
Muhammad Akram ◽  
Xindong Peng ◽  
Ahmad N. Al-Kenani ◽  
Aqsa Sattar
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Weighted Averaging ◽  
Two Dimensional ◽  
Fuzzy Information ◽  
Pythagorean Fuzzy Set ◽  
Priority Level ◽  
Prioritized Aggregation Operators

Complex Pythagorean fuzzy (CPF), a worthwhile generalization of Pythagorean fuzzy set, is a powerful tool to deal with two-dimensional or periodic information. In this paper, we develop two prioritized aggregation operators (AOs) under CPF environment, namely, complex Pythagorean fuzzy prioritized weighted averaging (CPFPWA) operator and complex Pythagorean fuzzy prioritized weighted geometric (CPFPWG) operator. We consider the prioritization relationship among criteria and decision makers (DMs) to make our result more accurate as in real decision making (DM) problems, the criteria and DMs have different priority level. Further, we discuss remarkable properties of our proposed AOs. Moreover, we promote the evolution of MCDM problem by investigating an algorithm in CPF environment with its flow chart. Finally, to check the superiority and validity of proposed operators, we compare the computed results with the different existing techniques.

scholarly journals Extended VIKOR Method for Intuitionistic Fuzzy Multiattribute Decision-Making Based on a New Distance Measure

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Xiao Luo ◽  
Xuanzi Wang
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Decision Makers ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Vikor Method ◽  
Individual Decision ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy

An intuitionistic fuzzy VIKOR (IF-VIKOR) method is proposed based on a new distance measure considering the waver of intuitionistic fuzzy information. The method aggregates all individual decision-makers’ assessment information based on intuitionistic fuzzy weighted averaging operator (IFWA), determines the weights of decision-makers and attributes objectively using intuitionistic fuzzy entropy, calculates the group utility and individual regret by the new distance measure, and then reaches a compromise solution. It can be effectively applied to multiattribute decision-making (MADM) problems where the weights of decision-makers and attributes are completely unknown and the attribute values are intuitionistic fuzzy numbers (IFNs). The validity and stability of this method are verified by example analysis and sensitivity analysis, and its superiority is illustrated by the comparison with the existing method.

scholarly journals New Extended Topsis Method Based On The Entropy Measure And Picture Fuzzy Rough Set Information And Their Application In Decision Support System

2021 ◽  
Author(s):  
Muhammad Ali Khan ◽  
Saleem Abdullah ◽  
Abbas Qadir
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Score Function ◽  
Entropy Measure ◽  
Comparison Results ◽  
Multiple Attribute ◽  
Robot Selection

Abstract In this article, we shall introduce a novel technique for order preference by similarity to ideal solution (TOPSIS)-based methodology to resolve multicriteria group decision-making problems within picture fuzzy environment, where the weights information of both the decision makers (DMs) and criteria are completely unknown. First, we briefly review the definition of picture fuzzy sets (PFS), score function and accuracy function of PFRSs and their basic operational laws. In addition, defined the generalized distance measure for PFRSs based on picture fuzzy rough entropy measure to compute the unknown weights information. Secondly, the picture fuzzy information based decision-making technique for multiple attribute group decision making (MAGDM) is established and all computing steps are simply depicted. In our presented model, it's more accuracy and effective for considering the conflicting attributes. Finally, an illustrative example with robot selection is provided to demonstrate the effectiveness of the proposed picture fuzzy decision support approaches, together with comparison results discussion, proving that its results are feasible and credible.

scholarly journals Fuzzy Multi-Criteria Decision Making Algorithm under Intuitionistic Hesitant Fuzzy Set with Novel Distance Measure

2020 ◽  
Vol 5 (3) ◽  
pp. 473-487 ◽  
Author(s):  
Rupjit Saikia ◽  
Harish Garg ◽  
Palash Dutta
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Decision Makers ◽  
Distance Measures ◽  
Hesitant Fuzzy Set ◽  
Multi Criteria Decision Making ◽  
Crucial Issue ◽  
Decision Making Problem

Decision making under uncertainty is a crucial issue and most demanding area of research now a days. Intuitionistic hesitant fuzzy set plays important role in dealing with the circumstances in which decision makers judge an alternative with a collection membership grades and a collection of non-membership grades. This paper contributes a novel and advanced distance measure between Intuitionistic Hesitant fuzzy sets (IHFSs). A comparative analysis of the present distance measure with existing measures is performed first. Afterwards, a case study is carried in multi-criteria decision making problem to exhibit the applicability and rationality of the proposed distance measure. The advantage of the proposed distance measure over the existing distance measures is that in case of deficit number of elements in IHFs, a decision maker can evaluate distance measure without adding extra elements to make them equivalent and furthermore, it works in successfully in all the situations.

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