scholarly journals Multi-Attribute Decision Making Method Based on Neutrosophic Vague N-Soft Sets

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 853 ◽  
Author(s):  
Jianbo Liu ◽  
Yanan Chen ◽  
Ziyue Chen ◽  
Yanyan Zhang
Keyword(s):  
Decision Making ◽  
Hybrid Model ◽  
Membership Function ◽  
Potential Application ◽  
Daily Life ◽  
Soft Sets ◽  
Vague Sets ◽  
Multi Attribute Decision Making ◽  
Priority Relation ◽  
First Time

This paper proposes neutrosophic vague N-soft sets which is composed of neutrosophic vague sets and N-soft sets for the first time. The new hybrid model includes a pair of asymmetric functions: truth-membership and false-membership, and an indeterminacy-membership function. Some useful operations and propositions are given and illustrated by examples. Moreover, a method of priority relation ranking based on neutrosophic vague N-soft sets is presented. The validity of the method is verified by comparison. It is more flexible and reasonable to use this method in our daily life. Finally, a potential application of multi-attribute decision making is presented.

scholarly journals Decision-Making Analysis Based on Hesitant Fuzzy N-Soft ELECTRE-I Approach

2021 ◽  
Author(s):  
Arooj Adeel ◽  
Muhammad Akram ◽  
Naim Cagman
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set Theory ◽  
Uncertain Data ◽  
Hesitant Fuzzy Set ◽  
Topsis Method ◽  
Soft Sets ◽  
Research Article ◽  
Electre I ◽  
Multi Attribute Decision Making

Abstract For the formal expression of uncertain data, hesitant fuzzy set theory has established itself as a distinguished model because it has a broad use in multi-attribute decision-making problems. With the incorporation of features from N -soft sets, a useful framework referred to as hesitant fuzzy N -soft sets has acquired an even greater appeal. This model integrates and associates the hesitant environment with information regarding the existence of grades or star ratings. In this research article, we introduce a multi-attribute decision-making technique known as hesitant fuzzy N -soft ELECTRE-I, which computes the decision-maker assessments in an adjustable and formative manner. The proposed method also improves the robustness and accuracy of the decisions relying on grades or star ratings. Thus it lays a bedrock for subsequent analyses and applications. We justify the relevance and convenience of the proposed technique by testing it in actually existing scenarios. Finally, we give a comparison of this novel methodology with the HFNS-TOPSIS method.

scholarly journals Vector Similarity Measures of Q-Linguistic Neutrosophic Variable Sets and Their Multi-Attribute Decision Making Method

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 531 ◽  
Author(s):  
Jun Ye ◽  
Zebo Fang ◽  
Wenhua Cui
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Similarity Measures ◽  
Two Dimensional ◽  
Linguistic Terms ◽  
Multi Attribute Decision Making ◽  
First Time

Since language is used for thinking and expressing habits of humans in real life, the linguistic evaluation for an objective thing is expressed easily in linguistic terms/values. However, existing linguistic concepts cannot describe linguistic arguments regarding an evaluated object in two-dimensional universal sets (TDUSs). To describe linguistic neutrosophic arguments in decision making problems regarding TDUSs, this study proposes a Q-linguistic neutrosophic variable set (Q-LNVS) for the first time, which depicts its truth, indeterminacy, and falsity linguistic values independently corresponding to TDUSs, and vector similarity measures of Q-LNVSs. Thereafter, a linguistic neutrosophic multi-attribute decision-making (MADM) approach by using the presented similarity measures, including the cosine, Dice, and Jaccard measures, is developed under Q-linguistic neutrosophic setting. Lastly, the applicability and effectiveness of the presented MADM approach is presented by an illustrative example under Q-linguistic neutrosophic setting.

N-soft rough sets and its applications

2021 ◽  
Vol 40 (1) ◽  
pp. 565-573
Author(s):  
Di Zhang ◽  
Pi-Yu Li ◽  
Shuang An
Keyword(s):  
Decision Making ◽  
Hybrid Model ◽  
Rough Sets ◽  
Real Life ◽  
Decision Problems ◽  
Multi Criteria Decision Making ◽  
Approximation Space ◽  
Soft Sets ◽  
Approximation Operators ◽  
Rough Approximation

In this paper, we propose a new hybrid model called N-soft rough sets, which can be seen as a combination of rough sets and N-soft sets. Moreover, approximation operators and some useful properties with respect to N-soft rough approximation space are introduced. Furthermore, we propose decision making procedures for N-soft rough sets, the approximation sets are utilized to handle problems involving multi-criteria decision-making(MCDM), aiming at electing the optional objects and the possible optional objects based on their attribute set. The algorithm addresses some limitations of the extended rough sets models in dealing with inconsistent decision problems. Finally, an application of N-soft rough sets in multi-criteria decision making is illustrated with a real life example.

scholarly journals Another View of Aggregation Operators on Group-Based Generalized Intuitionistic Fuzzy Soft Sets: Multi-Attribute Decision Making Methods

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 753 ◽  
Author(s):  
Khizar Hayat ◽  
Muhammad Ali ◽  
Bing-Yuan Cao ◽  
Faruk Karaaslan ◽  
Xiao-Peng Yang
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Soft Set ◽  
Weighted Averaging ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

In this paper, the existing definition of the group-based generalized intuitionistic fuzzy soft set is clarified and redefined by merging intuitionistic fuzzy soft set over the set of alternatives and a group of intuitionistic fuzzy sets on parameters. In this prospect, two new subsets of the group-based generalized intuitionistic fuzzy soft set are proposed and several operations are contemplated. The two new aggregation operators called generalized group-based weighted averaging and generalized group-based weighted geometric operator are introduced. The related properties of proposed operators are discussed. The recent research is emerging on multi-attribute decision making methods based on soft sets, intuitionistic fuzzy soft sets, and generalized intuitionistic fuzzy soft sets. An algorithm is structured and two case studies of multi-attribute decision makings are considered using proposed operators. Further, we provide the comparison and advantages of the proposed method, which give superiorities over recent major existing methods.

Supplier/partner selection in agile supply chain

2016 ◽  
Vol 23 (4) ◽  
pp. 866-892 ◽  
Author(s):  
Chhabi Ram Matawale ◽  
Saurav Datta ◽  
S.S. Mahapatra
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Set Theory ◽  
Membership Function ◽  
Supplier Selection ◽  
Partner Selection ◽  
Content Type ◽  
Vague Set ◽  
Vague Sets ◽  
Agile Supply Chain

Purpose – The concept of agile supply chain (ASC) has become increasingly important as means of achieving a competitive edge in turbulent business environments. An ASC is a dynamic alliance of member enterprises, the adaptation of which is likely to introduce velocity, responsiveness and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern; influenced by various agility-related criteria/attributes. Therefore, evaluation and selection of potential supplier in an ASC has become an important multi-criteria decision-making problem. The purpose of this paper is to report, a supplier selection procedure (module) in the context of ASC. Design/methodology/approach – During supplier selection, subjectivity of evaluation information (human judgment) often creates conflict and bears some kind of uncertainty. To overcome this, the present work attempts to explore vague set theory to deal with uncertainties in the supplier selection decision-making process. Since, vague sets can provide more accurate information as compared to fuzzy sets. It considers true membership function as well as false membership function which give more superior results for uncertain information. In this procedure, first, linguistic variables have been used to assess appropriateness rating (performance extent) as well as priority weights for individual quantitative or qualitative criterions. Second, the concept of degree of similarity and probability of vague sets has been used to determine appropriate ranking order of the potential supplier alternatives. Findings – A case empirical example has been provided. It has been proved that the methodology would be fruitful in considering different evaluation criterion (indices); may be contradicting in nature like beneficial and cost criterions. The application of vague set theory has also been proved as a better option to work under uncertain (fuzzy) decision-making environment in comparison to fuzzy set theory. Originality/value – The application of vague set theory in multi-criteria group decision making has been reported in literature to a limited extent. Application of vague set as a decision-making tool in agile supplier selection appears relative new and unexplored work area. The work has got remarkable managerial implications.

scholarly journals Intuitionistic Fuzzy (IF) Overlap Functions and IF-Rough Sets with Applications

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1494
Author(s):  
Xiaofeng Wen ◽  
Xiaohong Zhang ◽  
Tao Lei
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Fuzzy Topsis ◽  
Theoretical Research ◽  
New Class ◽  
Intuitionistic Fuzzy ◽  
Generating Method ◽  
Multi Attribute Decision Making ◽  
Intuitionistic Fuzzy Topsis ◽  
First Time

Overlap function (which has symmetry and continuity) is widely used in image processing, data classification, and multi-attribute decision making problems. In recent years, theoretical research on overlap function has been extended to interval valued overlap function and lattice valued overlap function, but intuitionistic fuzzy overlap function (IF-overlap function) has not been studied. In this paper, the concept of IF-overlap function is proposed for the first time, then the generating method of IF-overlap function is given. The representable IF-overlap function is defined, and the concrete examples of representable and unrepresentable IF-overlap functions are given. Moreover, a new class of intuitionistic fuzzy rough set (IF-roght set) model is proposed by using IF-overlap function and its residual implication, which extends the IF-rough set model based on intuitionistic fuzzy triangular norm, and the basic properties of the new intuitionistic fuzzy upper and lower approximate operators are analyzed and studied. At the same time, the established IF-rough set based on IF-overlap function is applied to MCDM (multi-criteria decision-making) problems, the intuitionistic fuzzy TOPSIS method is improved. Through the comparative analysis of some cases, the new method is proved to be flexible and effective.

On pythagorean fuzzy soft topological spaces

2021 ◽  
pp. 1-9
Author(s):  
Ibtesam Alshammari ◽  
Mani Parimala ◽  
Saeid Jafari
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Topological Spaces ◽  
Decision Making Process ◽  
Soft Sets ◽  
New Methods ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Fuzzy Soft Sets

Imprecision in the decision-making process is an essential consideration. In order to navigate the imprecise decision-making framework, measuring tools and methods have been developed. Pythagorean fuzzy soft sets are one of the new methods for dealing with imprecision. Pythagorean fuzzy soft topological spaces is an extension of intuitionistic fuzzy soft topological spaces. These sets generalizes intuitionistic fuzzy sets for a broader variety of implementations. This work is a gateway to study such a problem. The concept of Pythagorean fuzzy soft topological spaces(PyFSTS), interior, closure, boundary, neighborhood of Pythagorean fuzzy soft spaces PyFSS, base and subspace of PyFSTSs are presented and its properties are figured out. We established an algorithm under uncertainty based on PyFSTS for multi-attribute decision-making (MADM) and to validate this algorithm, a numerical example is solved for suitable brand selection. Finally, the benefits, validity, versatility and comparison of our proposed algorithms with current techniques are discussed.The advantage of the proposed work is to detect vagueness with more sizably voluminous valuation space than intuitionistic fuzzy sets.

Grey risky multi-attribute decision-making method based on regret theory and EDAS

2019 ◽  
Vol 9 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Lili Qian ◽  
Sifeng Liu ◽  
Zhigeng Fang
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Decision Makers ◽  
Regret Theory ◽  
Ranking Problem ◽  
Content Type ◽  
Multi Attribute Decision Making ◽  
Method Of Evaluation ◽  
Regret Aversion ◽  
First Time

Purpose The purpose of this paper is to advance a new grey risky multi-attribute decision-making (RMADM) method from the perspective of regret aversion, which is based on the general grey numbers (GGNs) taking the form of kernel and degree of greyness. Design/methodology/approach First, the normalised grey decision-making matrix is obtained on the basis of kernel and greyness degree of GGNs. Then the regret theory is integrated into the decision-making process by constructing the grey perceived utility function based on GGNs. Finally, the method of evaluation based on distance from average solution (EDAS) is applied to handle with the ranking problem because of its efficiency, stability as well as simplicity. Findings GGNs have more powerful capacity in expressing uncertainty than interval grey numbers, so the method can solve a larger number of RMADM problems in uncertain and imprecise environments. Meanwhile, the method fully considers the psychological behaviour of the decision makers, which is more applicable to the real world. It is the supplement and perfection of the existing RMADM methods. Originality/value The RMADM problem, the grey regret-rejoice function and the EDAS method are all introduced for the first time with GGNs in the form of kernel and degree of greyness. At the same time, the EDAS method is also the first time to be used in combination with the grey RMADM method based on the regret theory.

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