scholarly journals Variances and Logarithmic Aggregation Operators: Extended Tools for Decision-Making Processes

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1892
Author(s):  
Rodrigo Gómez Monge ◽  
Evaristo Galeana Figueroa ◽  
Víctor G. Alfaro-García ◽  
José M. Merigó ◽  
Ronald R. Yager

Variance, as a measurement of dispersion, is a basic component of decision-making processes. Recent advances in intelligent systems have included the concept of variance in information fusion techniques for decision-making under uncertainty. These dispersion measures broaden the spectrum of decision makers by extending the toolset for the analysis and modeling of problems. This paper introduces some variance logarithmic averaging operators, including the variance generalized ordered weighted averaging (Var-GOWLA) operator and the induced variance generalized ordered weighted averaging (Var-IGOWLA) operator. Moreover, this paper analyzes some properties, families and particular cases of the proposed operators. Finally, an illustrative example of the characteristic design of the operators is proposed using real-world information retrieved from financial markets. The objective of this paper is to analyze the performance of some equities based on the expected payoff and the dispersion of its elements. Results show that the equity payoff results present diverse rankings combined with the proposed operators, and the introduced variance measures aid decision-making by offering new tools for information analysis. These results are particularly interesting when selecting logarithmic averaging operators for decision-making processes. The approach presented in this paper extends the available tools for decision-making under ignorance, uncertainty, and subjective environments.

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 180 ◽  
Author(s):  
Aliya Fahmi ◽  
Fazli Amin ◽  
Madad Khan ◽  
Florentin Smarandache

In this paper, a new concept of the triangular neutrosophic cubic fuzzy numbers (TNCFNs), their score and accuracy functions are introduced. Based on TNCFNs, some new Einstein aggregation operators, such as the triangular neutrosophic cubic fuzzy Einstein weighted averaging (TNCFEWA), triangular neutrosophic cubic fuzzy Einstein ordered weighted averaging (TNCFEOWA) and triangular neutrosophic cubic fuzzy Einstein hybrid weighted averaging (TNCFEHWA) operators are developed. Furthermore, their application to multiple-attribute decision-making with triangular neutrosophic cubic fuzzy (TNCF) information is discussed. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.


Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 698 ◽  
Author(s):  
Muhammad Jamil ◽  
Saleem Abdullah ◽  
Muhammad Yaqub Khan ◽  
Florentin Smarandache ◽  
Fazal Ghani

The present study aims to introduce the notion of bipolar neutrosophic Hamacher aggregation operators and to also provide its application in real life. Then neutrosophic set (NS) can elaborate the incomplete, inconsistent, and indeterminate information, Hamacher aggregation operators, and extended Einstein aggregation operators to the arithmetic and geometric aggregation operators. First, we give the fundamental definition and operations of the neutrosophic set and the bipolar neutrosophic set. Our main focus is on the Hamacher aggregation operators of bipolar neutrosophic, namely, bipolar neutrosophic Hamacher weighted averaging (BNHWA), bipolar neutrosophic Hamacher ordered weighted averaging (BNHOWA), and bipolar neutrosophic Hamacher hybrid averaging (BNHHA) along with their desirable properties. The prime gain of utilizing the suggested methods is that these operators progressively provide total perspective on the issue necessary for the decision makers. These tools provide generalized, increasingly exact, and precise outcomes when compared to the current methods. Finally, as an application, we propose new methods for the multi-criteria group decision-making issues by using the various kinds of bipolar neutrosophic operators with a numerical model. This demonstrates the usefulness and practicality of this proposed approach in real life.


Author(s):  
Meimei Xia

The target-oriented multi-criteria decision making is investigated based on the ordered weighted averaging (OWA) operator. The criteria evaluations are measured by using the likelihood of satisfying the targets of criteria. To aggregate the target-oriented criteria evaluations, the target-oriented OWA operator is firstly introduced, in which the target-oriented criteria evaluations are reordered and then aggregated by using the weight vector associated with the position of criteria evaluations. Four types of targets about criteria evaluations and four types of attitudinal characters about criteria weight vector are introduced, based on which, models are given to identify the potential best alternative(s), and estimate the ranges of attitudinal characters about criteria weight vector for each potential best alternative. The proposed models can not only analyze the sensitivity of each potential best alternative, but also can explore the impact of targets about criteria evaluations and attitudinal characters about criteria weight vector on the decision results. Models are further established to find the best and worst ranking orders of each alternative based on targets about criteria evaluations, and give decision analysis by considering specific ranking orders of alternatives. The proposed method considers the targets about criteria evaluations and attitudinal character about criteria weight vector at the same time and can provide decision makers more choices. Several examples are given to illustrate the proposed methods.


Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 658 ◽  
Author(s):  
Aliya Fahmi ◽  
Fazli Amin ◽  
Florentin Smarandache ◽  
Madad Khan ◽  
Nasruddin Hassan

In this paper, triangular cubic hesitant fuzzy Einstein weighted averaging (TCHFEWA) operator, triangular cubic hesitant fuzzy Einstein ordered weighted averaging (TCHFEOWA) operator and triangular cubic hesitant fuzzy Einstein hybrid weighted averaging (TCHFEHWA) operator are proposed. An approach to multiple attribute group decision making with linguistic information is developed based on the TCHFEWA and the TCHFEHWA operators. Furthermore, we establish various properties of these operators and derive the relationship between the proposed operators and the existing aggregation operators. Finally, a numerical example is provided to demonstrate the application of the established approach.


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