Results 21 to 30 of about 5,704 (305)

The Economic Order Quantity in a Fuzzy Environment for a Periodic Inventory Model with Variable Demand

open access: yesIraqi Journal for Computer Science and Mathematics, 2022
The technique of limiting expenditure plays a critical part in an organization's ability to govern the smooth operation of its management system. The economic order quantity (EOQ) is calculated by solving a nonlinear problem, and the best solution is ...
K. Kalaiarasi   +3 more
doaj   +1 more source

Comparison of triangular fuzzy numbers

open access: yesVestnik Udmurtskogo Universiteta. Matematika. Mekhanika. Komp'yuternye Nauki, 2019
The concept of \textit{fuzzy set} of [\textit{L. A. Zadeh}, Inf. Control 8, 338--353 (1965; Zbl 0139.24606)] motivated the development of fuzzy real analysis. In particular, the notion of \textit{fuzzy number} was introduced and basic operations with such new structures were considered (see, e.g., [\textit{D. Dubois} and \textit{H. Prade}, in: Analysis
Ukhobotov, Viktor Ivanovich   +2 more
openaire   +3 more sources

On the notion of fuzzy dispersion measure and its application to triangular fuzzy numbers

open access: yesInformation Fusion, 2023
In this paper, based on the analysis of the most widely used dispersion measure in the real context (namely, the variance), we introduce the notion of fuzzy dispersion measure associated to a finite set of data given by fuzzy numbers. This measure is implemented as a fuzzy number, so there is no loss of information caused by any defuzzification.
Antonio-Francisco Roldán-López-de-Hierro   +5 more
openaire   +4 more sources

The membership function of a triangular fuzzy number.

open access: yes, 2023
The membership function of a triangular fuzzy number.
Yang-Cheng Lin (16877739)   +2 more
core   +1 more source

Fuzzy Autoregressive Time Series Model Based on Symmetry Triangular Fuzzy Numbers [PDF]

open access: yes, 2021
The symmetry triangular fuzzy number has been developed to build fuzzy autoregressive models by using various approaches such as low-high data, integer number, measurement error, and standard deviation data.
Suhartono, Suhartono   +6 more
core   +1 more source

Solving Fully Fuzzy Linear Programming Problems with Zero-One Variables by Ranking Function [PDF]

open access: yesControl and Optimization in Applied Mathematics, 2016
Jahanshahloo has suggested a method for the solving linear programming problems with zero-one variables. In this paper we formulate fully fuzzy linear programming problems with zero-one variables and a method for solving these problems is presented using
Aminalah Alba
doaj  

Aggregation Operators on Triangular Intuitionistic Fuzzy Numbers and its Application to Multi-Criteria Decision Making Problems

open access: yesFoundations of Computing and Decision Sciences, 2014
The aim of this work is to present some aggregation operators with triangular intuitionistic fuzzy numbers and study their desirable properties. Firstly, the score function and the accuracy function of triangular intuitionistic fuzzy number are given ...
Liang Changyong   +2 more
doaj   +1 more source

Autoregressive modeling with error percentage spread based triangular fuzzy number [PDF]

open access: yes, 2019
Data collected by various methods are often prone to uncertainty of measurement which may affect the information conveyed by the quantitative result.
Chai Wen, Chuah   +3 more
core   +1 more source

Seaport Network Efficiency Measurement Using Triangular and Trapezoidal Fuzzy Data Envelopment Analyses with Liner Shipping Connectivity Index Output

open access: yes, 2023
Seaport network efficiency is very crucial for global maritime economic trades and growth. In this work, data of three years (2018–2020) with input variables (time in port, age of vessels, size of vessels, cargo carrying capacity of vessels) and ...
Noor Fadiya Mohd Noor   +2 more
core   +1 more source

An Approach to the Total Least Squares Method for Symmetric Triangular Fuzzy Numbers

open access: yesMathematics
The total least squares method has a broad applicability in many fields. It is also useful in fuzzy data analysis. In this paper, we study the method of total least squares for fuzzy variables. The regression parameters are considered to be crisp. First,
Marius Giuclea, Costin-Ciprian Popescu
doaj   +1 more source

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