scholarly journals Rough q-Rung Orthopair Fuzzy Sets and Their Applications in Decision-Making

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2010
Author(s):  
Muhammad Asim Bilal ◽  
Muhammad Shabir ◽  
Ahmad N. Al-Kenani
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Vital Role ◽  
Optimal Decision ◽  
Final Decision ◽  
Pythagorean Fuzzy Set ◽  
Accuracy Measure

Yager recently introduced the q-rung orthopair fuzzy set to accommodate uncertainty in decision-making problems. A binary relation over dual universes has a vital role in mathematics and information sciences. During this work, we defined upper approximations and lower approximations of q-rung orthopair fuzzy sets using crisp binary relations with regard to the aftersets and foresets. We used an accuracy measure of a q-rung orthopair fuzzy set to search out the accuracy of a q-rung orthopair fuzzy set, and we defined two types of q-rung orthopair fuzzy topologies induced by reflexive relations. The novel concept of a rough q-rung orthopair fuzzy set over dual universes is more flexible when debating the symmetry between two or more objects that are better than the prevailing notion of a rough Pythagorean fuzzy set, as well as rough intuitionistic fuzzy sets. Furthermore, using the score function of q-rung orthopair fuzzy sets, a practical approach was introduced to research the symmetry of the optimal decision and, therefore, the ranking of feasible alternatives. Multiple criteria decision making (MCDM) methods for q-rung orthopair fuzzy sets cannot solve problems when an individual is faced with the symmetry of a two-sided matching MCDM problem. This new approach solves the matter more accurately. The devised approach is new within the literature. In this method, the main focus is on ranking and selecting the alternative from a collection of feasible alternatives, reckoning for the symmetry of the two-sided matching of alternatives, and providing a solution based on the ranking of alternatives for an issue containing conflicting criteria, to assist the decision-maker in a final decision.

Multiple criteria decision making based on Hamy mean operators under the environment of spherical fuzzy sets

2021 ◽  
pp. 1-26
Author(s):  
Muhammad Sarwar Sindhu ◽  
Tabasam Rashid ◽  
Agha Kashif
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Closed Interval ◽  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Vital Role ◽  
Multiple Criteria ◽  
Uncertain Information ◽  
Membership Degree ◽  
Picture Fuzzy Sets

Aggregation operators are widely applied to accumulate the vague and uncertain information in these days. Hamy mean (HM) operators play a vital role to accumulate the information. HM operators give us a more general and stretchy approach to develop the connections between the arguments. Spherical fuzzy sets (SpFSs), the further extension of picture fuzzy sets (PcFSs) that handle the data in which square sum of membership degree (MD), non-membership degree (NMD) and neutral degree (ND) always lie between closed interval [0, 1]. In the present article, we modify the HM operators like spherical fuzzy HM (SpFHM) operator and weighted spherical fuzzy HM (WSpFHM) operator to accumulate the spherical fuzzy (SpF) information. Moreover, various properties and some particular cases of SpFHM and the WSpFHM operators are discussed in details. Also, to compare the results obtained from the HM operators a score function is developed. Based on WSpFHM operator and score function, a model for multiple criteria decision-making (MCDM) is established to resolve the MCDM problem. To check the significance and robustness of the result, a comparative analysis and sensitivity analysis is also performed.

scholarly journals Extended Fuzzy Sets and Their Applications

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 770
Author(s):  
Bahram Farhadinia ◽  
Francisco Chiclana
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Score Function ◽  
Pythagorean Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Algebraic Operations ◽  
Innovative Concept

This contribution deals with introducing the innovative concept of extended fuzzy set (E-FS), in which the S-norm function of membership and non-membership grades is less than or equal to one. The proposed concept not only encompasses the concept of the fuzzy set (FS), but it also includes the concepts of the intuitionistic fuzzy set (IFS), the Pythagorean fuzzy set (PFS) and the p-rung orthopair fuzzy set (p-ROFS). In order to explore the features of the E-FS concept, set and algebraic operations on E-FSs, average and geometric operations of E-FSs are studied and an E-FS score function is defined. The superiority of the E-FS concept is further confirmed with a score-based decision making technique in which the concepts of FS, IFS, PFS and p-ROFS do not make sense.

Approximations of pythagorean fuzzy sets over dual universes by soft binary relations

2021 ◽  
pp. 1-17
Author(s):  
Muhammad Asim Bilal ◽  
Muhammad Shabir
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Binary Relations ◽  
Pythagorean Fuzzy Set ◽  
Course Of Action ◽  
Proposed Model ◽  
Accuracy Measure ◽  
Lower And Upper Approximations ◽  
Selection Of

 Yager introduced the Pythagorean Fuzzy Set (PFS) to deal with uncertainty in real-world decision-making problems. Binary relations play an important role in mathematics as well as in information sciences. Soft binary relations give us a parameterized collection of binary relations. In this paper, lower and upper approximations of PFSs based on Soft binary relations are given with respect to the aftersets and with respect to the foresets. Further, two kinds of Pythagorean Fuzzy Topologies induced by Soft reflexive relations are investigated and an accuracy measure of a PFS is provided. Besides, based on the score function and these approximations of PFSs, an algorithm is constructed for ranking and selection of the decision-making alternatives. Although many MCDM (multiple criteria decision making) methods for PFSs have been proposed in previous studies, some of those cannot solve when a person is encountered with a two-sided matching MCDM problem. The proposed method is new in the literature. This newly proposed model solved the problem more accurately. The proposed method focuses on selecting and ranking from a set of feasible alternatives depending on the two-sided matching of attributes and determines a ranking based solution for a problem with conflicting criteria to help the decision-maker in reaching a final course of action.

scholarly journals MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luis Pérez-Domínguez ◽  
Luis Alberto Rodríguez-Picón ◽  
Alejandro Alvarado-Iniesta ◽  
David Luviano Cruz ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Multiobjective Optimization ◽  
Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Ratio Analysis ◽  
Pythagorean Fuzzy Set ◽  
Decision Making Problem ◽  
Moora Method

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method.

Graded Soft Expert Set as a Generalization of Hesitant Fuzzy Set

2018 ◽  
Vol 29 (1) ◽  
pp. 223-236
Author(s):  
Afshan Qayyum ◽  
Tanzeela Shaheen
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Vital Role ◽  
Decision Makers ◽  
Hesitant Fuzzy Set ◽  
Relative Importance ◽  
Hesitant Fuzzy Sets

Abstract Hesitant fuzzy sets play a vital role in decision analysis. Although they have been proved to be a landmark in evaluating information, there are certain deficiencies in their structure. Also, in decision analysis with the aid of hesitant fuzzy sets, the relative importance of the decision makers according to their area of expertise is ignored completely, which may be misleading in some situations. These sorts of issues have been resolved in this work by using graded soft expert (GSE) sets. The proposed structure is a modified form of soft expert sets. Some basic operations have been introduced, and certain laws satisfied by them have carefully been investigated. With the aid of GSE sets, a decision-making algorithm (accompanied with an example) has been developed in which experts have been given due weightage according to their area of expertise.

Approaches to Multi-Attribute Group Decision Making Based on Induced Interval-Valued Pythagorean Fuzzy Einstein Aggregation Operator

2018 ◽  
Vol 14 (03) ◽  
pp. 343-361 ◽  
Author(s):  
K. Rahman ◽  
A. Ali ◽  
S. Abdullah ◽  
F. Amin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Vital Role ◽  
Aggregation Operator ◽  
Weighted Averaging ◽  
Pythagorean Fuzzy Set ◽  
Interval Valued

Interval-valued Pythagorean fuzzy set is one of the successful extensions of the interval-valued intuitionistic fuzzy set for handling the uncertainties in the data. Under this environment, in this paper, we introduce the notion of induced interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (I-IVPFEOWA) aggregation operator. Some of its desirable properties namely, idempotency, boundedness, commutatively, monotonicity have also been proved. The main advantage of using the proposed operator is that this operator gives a more complete view of the problem to the decision-makers. The method proposed in this paper provides more general, more accurate and precise results as compared to the existing methods. Therefore this method play a vital role in real world problems. Finally, we apply the proposed operator to deal with multi-attribute group decision- making problems under interval-valued Pythagorean fuzzy information. The approach has been illustrated with a numerical example from the field of the decision-making problems to show the validity, practicality and effectiveness of the new approach.

scholarly journals A New Multiple Criteria Decision Making Method and its Application in Cloud Computing for Education

2015 ◽  
Vol 10 (8) ◽  
pp. 21
Author(s):  
Heng Sun
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Membership Function ◽  
Fuzzy Set ◽  
Choquet Integral ◽  
Intuitionistic Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Multiple Criteria ◽  
Intuitionistic Fuzzy

Cloud computing can extend the traditional education framework. In education, cloud can provide students and teachers with tools to deploy computing resources on-demand for lectures and labs according to their learning needs. But how to select a perfect cloud server is a key point, which is considered as a multiple criteria decision making problem. So, in this paper, intuitionistic fuzzy set is first introduced to express the decision maker’s views. Intuitionistic fuzzy set (IFS) includes a membership function and a non-membership function. More importantly, a new operator with choquet integral is developed to deal with assessment of education using cloud computing. Meanwhile, score function and accuracy function are demonstrated to obtain the final result. Finally, we develop this method to apply in a case study to show its applicability.

scholarly journals Application of Pythagorean Fuzzy Digraphs in Package Delivery Robots

2021 ◽  
Author(s):  
Kanagaraj Sangeetha ◽  
◽  
Mani X Mani Parimala ◽  
Mohammed A. Al Shumrani ◽  
Said Broumi ◽  
...  
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Driving Forces ◽  
Intuitionistic Fuzzy Set ◽  
Score Function ◽  
Fuzzy Graph ◽  
Pythagorean Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Package Delivery ◽  
Vertex Set

The fuzzy set concept was developed to cope with uncertainty, whereas traditional sets are intended to deal with certainty. To address flaws in fuzzy set theory, extensions such as Intuitionistic Fuzzy Set (IFS), neutrosophic fuzzy sets, image fuzzy sets, and Pythagorean fuzzy set (PyFS) were developed. Pythagorean fuzzy set is useful tool for more clearly defining hazy concepts. In comparison to other fuzzy models, Pythagorean fuzzy set-based models allow more flexibility in handling human judgement information. The fuzzy graph structure is used to deal with the uncertainty in a network and to characterize its relationship with the non-empty vertex set. Pythagorean fuzzy graph (PyFG) was one of the Intuitionistic Fuzzy Graph (IFG) extensions. PyFG was created to cope with the uncertainty of an object and its relationship with other objects. PyFS and PyFG are the driving forces behind this innovative concept. This work defines Pythagorean Fuzzy Digraph (PyFDG), and PyFDG's score function. An algorithm is proposed for an issue to find the Pythagorean shortest path in package delivery robots.

scholarly journals Hesitant Bipolar-Valued Fuzzy Soft Sets and Their Application in Decision Making

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jin-Ying Wang ◽  
Yan-Ping Wang ◽  
Lei Liu
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Score Function ◽  
Soft Set ◽  
Mathematical Tool ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Fuzzy Soft Sets

As an extension of fuzzy sets, hesitant bipolar-valued fuzzy set is a new mathematical tool for dealing with fuzzy problems, but it still has the problem with the inadequacy of the parametric tools. In order to further improve the accuracy of decision making, a new mixed mathematical model, named hesitant bipolar-valued fuzzy soft set, is constructed by combining hesitant bipolar-valued fuzzy sets with soft sets. Firstly, some related theories of hesitant bipolar-valued fuzzy sets are discussed. Secondly, the concept of hesitant bipolar-valued fuzzy soft set is given, and the algorithms of complement, union, intersection, “AND,” and “OR” are defined. Based on the above algorithms, the corresponding results of operation are analyzed and the relevant properties are discussed. Finally, a multiattribute decision-making method of hesitant bipolar-valued fuzzy soft sets is proposed by using the idea of score function and level soft sets. The effectiveness of the proposed method is illustrated by an example.

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