Fuzzy betweenness relations and their connection with fuzzy order relations

2020 ◽  
Vol 384 ◽  
pp. 1-22 ◽  
Author(s):  
Hua-Peng Zhang ◽  
Raúl Pérez-Fernández ◽  
Bernard De Baets
Keyword(s):  
Order Relations ◽  
Fuzzy Order ◽  
Betweenness Relations

scholarly journals New Hermite–Hadamard Inequalities in Fuzzy-Interval Fractional Calculus and Related Inequalities

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 673
Author(s):  
Muhammad Bilal Khan ◽  
Pshtiwan Othman Mohammed ◽  
Muhammad Aslam Noor ◽  
Y. S. Hamed
Keyword(s):  
Order Relation ◽  
Fractional Integrals ◽  
Order Relations ◽  
Inequality Theory ◽  
Real World Applications ◽  
Mathematical Problems ◽  
Interval Space ◽  
Fuzzy Order ◽  
Interval Valued ◽  
Fuzzy Interval

It is a familiar fact that inequalities have become a very popular method using fractional integrals, and that this method has been the driving force behind many studies in recent years. Many forms of inequality have been studied, resulting in the introduction of new trend in inequality theory. The aim of this paper is to use a fuzzy order relation to introduce various types of inequalities. On the fuzzy interval space, this fuzzy order relation is defined level by level. With the help of this relation, firstly, we derive some discrete Jensen and Schur inequalities for convex fuzzy interval-valued functions (convex fuzzy-IVF), and then, we present Hermite–Hadamard inequalities (-inequalities) for convex fuzzy-IVF via fuzzy interval Riemann–Liouville fractional integrals. These outcomes are a generalization of a number of previously known results, and many new outcomes can be deduced as a result of appropriate parameter and real valued function selections. We hope that our fuzzy order relations results can be used to evaluate a number of mathematical problems related to real-world applications.

INVOLVING FUZZY ORDERS FOR MULTI-OBJECTIVE LINEAR PROGRAMMING

2012 ◽  
Vol 17 (3) ◽  
pp. 366-382 ◽  
Author(s):  
Olga Grigorenko
Keyword(s):  
Linear Programming ◽  
Order Relation ◽  
Fuzzy Relation ◽  
Membership Functions ◽  
Objective Functions ◽  
Solution Approach ◽  
Multi Objective ◽  
Order Relations ◽  
The Individual ◽  
Fuzzy Order

This paper presents a solution approach for multi-objective linear programming problem. We propose to involve fuzzy order relations to describe the objective functions where in ”classical” fuzzy approach the membership functions which illustrate how far the concrete point is from the solution of individual problem are studied. Further the global fuzzy order relation is constructed by aggregating the individual fuzzy order relations. Thus the global fuzzy relation contains the information about all objective functions and in the last step we find a maximum in the set of constrains with respect to the global fuzzy order relation. We illustrate this approach by an example.

On the numerical semigroup generated by {bn+1+i+bn+i−1b−1∣i∈N}$\begin{array}{} \{b^{n+1+i}+\frac{b^{n+i}-1}{b-1}\mid i\in\mathbb{N}\} \end{array}$

2020 ◽  
Vol 30 (4) ◽  
pp. 257-264
Author(s):  
Ze Gu
Keyword(s):  
Numerical Semigroup ◽  
Frobenius Number ◽  
Embedding Dimension ◽  
Order Relations ◽  
Positive Integers

AbstractLet b, n be two positive integers such that b ≥ 2, and S(b, n) be the numerical semigroup generated by $\begin{array}{} \{b^{n+1+i}+\frac{b^{n+i}-1}{b-1}\mid i\in\mathbb{N}\} \end{array}$. Applying two order relations, we give formulas for computing the embedding dimension, the Frobenius number, the type and the genus of S(b, n).

An approach for supplier selection problem based on picture cubic fuzzy aggregation operators

2021 ◽  
Vol 40 (5) ◽  
pp. 10145-10162
Author(s):  
Ahmad Bakr Khoshaim ◽  
Muhammad Qiyas ◽  
Saleem Abdullah ◽  
Muhammad Naeem ◽  
Muneeza
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Numerical Application ◽  
Chain Management ◽  
Fuzzy Environment ◽  
Picture Fuzzy Set ◽  
Fuzzy Aggregation ◽  
Fuzzy Order

This article is an advanced approach to picture fuzzy set through the application of cubic set theory. For instance, we establish the idea of the picture cubic fuzzy sets (PCFSs) theory and define several operations for PCFS. Also, presented some weighted aggregation operators under picture cubic fuzzy information, so called picture cubic fuzzy weighted averaging (PCFWA) operator, picture cubic fuzzy order weighted averaging (PCFOWA) operator, picture cubic fuzzy weighted geometric (PCFWG) operator, and picture cubic fuzzy order weighted geometric (PCFOWG) operator. Further, we study their fundamental properties and showed the relationship among these aggregation operators. In order to determine the feasibility and practicality of the mentioned new technique, we developed multi-attribute group decision -making algorithm with picture cubic fuzzy environment. Further, the developed method applied to supply chain management and for implementation, consider numerical application of supply chain management. Compared the developed approach with other preexisting aggregation operators, and we concluded that the defined technique is better, reliable and effective.

Personality and psychopathology: Higher order relations between the five factor model of personality and the MMPI-2 Restructured Form

2013 ◽  
Vol 47 (5) ◽  
pp. 572-579 ◽  
Author(s):  
Paul T. van der Heijden ◽  
Gina M.P. Rossi ◽  
William M. van der Veld ◽  
Jan J.L. Derksen ◽  
Jos I.M. Egger
Keyword(s):  
Factor Model ◽  
Five Factor Model ◽  
Higher Order ◽  
Order Relations
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