Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
A New Approach for Solving Interval Neutrosophic Integer Programming Problems
1
11
EN
Seyed Mohammadtaghi
Azimi
Department of civil engineering,Guangzhou University,Guangzhou, China
m.azimi@e.gzhu.edu.cn
Hu
Chun
Department o civil engineering, Guangzhou University, Guangzhou, China
huchon@gzhu.edu.cn
Chen
Zhihong
Department of Civil Engineering,Guangzhou University,Guangzhou,China
chenzhihong1227@sina.com
Amirhossein
Nafei
Department of Mathematics and Information Science, Guangzhou University, Guangzhou,China
amir.nafei@e.gzhu.edu.cn
10.30495/fomj.2021.1926842.1025
A B S T R A C T<br />Linear Programming as a practical technique for solving optimization problems with linear objective functions and linear constraint plays an essential role in mathematical programming. Most of the real-world problems are included in inconsistent and astute uncertainty. That's why the optimal solution can't be found easily. The Neutrosophic theory, as an extension of fuzzy set theory, is a powerful instrument to handle inconsistent, indeterminate, and incomplete information. This paper presents an applied approach for solving Interval Neutrosophic Integer Programming problems. By using the proposed approach, we can handle both incomplete and indeterminate data. In this respect, using a ranking function, we present a technique to convert the Interval Neutrosophic Integer Programming problem into a crisp model and then solve it by standard methods.
Neutrosophic,linear programming,Integer programming,Interval neutrosophic number
http://fomj.qaemiau.ac.ir/article_681920.html
http://fomj.qaemiau.ac.ir/article_681920_0d41feedeb1e3ebfd9fe73cacfdb29a4.pdf
Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
Optimistic and Pessimistic Fuzzy Data Envelopment Analysis: Empirical Evidence from Tehran Stock Market
12
21
EN
Pejman
Peykani
0000-0001-7486-6796
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
pejman.peykani@yahoo.com
Mohammad
Namakshenas
School of Industrial Engineering,
Iran University of Science and Technology, Tehran, Iran
m_namakshenas@ind.iust.ac.ir
Nasim
Arabjazi
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
nasimarabjazy@gmail.com
Fatemeh
Shirazi
Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran
fsshirazi@aut.ac.ir
Neda
Kavand
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
nedakavand368@gmail.com
10.30495/fomj.2021.1931398.1028
In this paper, the fuzzy chance-constrained data envelopment analysis (FCCDEA) approach is presented for stock evaluation and portfolio selection under data ambiguity. To propose FCCDEA method, data envelopment analysis (DEA), possibilistic programming (PP), and chance-constrained programming (CCP) approaches are applied. It should be noted that FCCDEA models can be used by decision makers (DMs) under optimistic and pessimistic viewpoints. To show the applicability of the proposed fuzzy chance-constrained DEA approach, FCCDEA models based on possibility and necessity measures are implemented in a real-life case study from Tehran stock market. The results show the efficacy of the proposed FCCDEA approach for stock assessment in the presence of fuzzy data.
Fuzzy DEA,Possibility theory,Stock market,Data Ambiguity
http://fomj.qaemiau.ac.ir/article_682926.html
http://fomj.qaemiau.ac.ir/article_682926_6ce08dbdfb0cd068dab96a7a32b53977.pdf
Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
Considering the Criteria interdependency in the Matrix Approach to Robustness Analysis with Applying Fuzzy ANP
22
33
EN
Ali
Sorourkhah
0000000249615941
Department of Management, Ayandegan Institute of Higher Education, Tonekabon, Iran
ali.sorourkhah@gmail.com
Seyyed Ahmad
Edalatpanah
0000-0001-9349-5695
Department of Applied Mathematics, Ayandegan Institute of Higher Education, Tonekabon, Iran
saedalatpanah@aihe.ac.ir
10.30495/fomj.2021.1932066.1029
Choosing the appropriate strategy is the most vital decision for an organization. The real-world situation, comprising increasing criteria and alternatives; the criteria interdependency; environmental changes affecting the structure of the organization; the vagueness of the verbal judgments; and Increasing uncertainty about possible futures, forces the decision-makers to consider these two important elements, complexity and uncertainty, in their decision-making approach. While all of the most widely known approaches – the classic, scenario, MCDM, and robustness analysis approaches – have some weaknesses related to either complexity or uncertainty, the approach purposed in this study can overcome them, combining the matrix approach to the robustness analysis (MARA) with the fuzzy ANP method. This approach deals with the environmental uncertainty by reviewing the performance of the strategies among the alternative futures, the uncertainty related to the preference model of the human decision-maker (uncertain judgements) by using fuzzy set theory, specifically Chang’s extent analysis method, considers desired number of scenarios, criteria and options, and collects experts' judgments in an appropriate time, emphasizing interdependences among criteria. The proposed approach is applied to a real-world problem in the automotive industry of Iran and the results are compared with the previous studies.
decision making,Strategy Selection,Automotive Industry,Uncertainty and Complexity
http://fomj.qaemiau.ac.ir/article_683403.html
http://fomj.qaemiau.ac.ir/article_683403_bebf43285ee2cb1da1f841d822fdaf39.pdf
Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
Triangular Fuzzy Numbers Multiplication: QKB method
34
40
EN
Abdullah
Al-Qudaimi
Hodeidah University
aalqudaimi@yahoo.com
Kuljeet
Kaur
École de Technologie Supérieure (Université du Québec), Montréal, Canada
kuljeet.kaur@etsmtl.ca
Shahid
Bhat
Thapar Institute of Engineering and Technology, Patiala, India
bhatshahid444@gmail.com
10.30495/fomj.2021.1934118.1032
Triangular Fuzzy numbers (TFNs) are vast and common representation of fuzzy data in applied sciences. Multiplication is a very indispensable operation for fuzzy numbers. It is necessary to decompose fuzzy systems such as fully triangular fuzzy regression models where the unknown and unrestricted triangular fuzzy coefficients multiplied by known TFNs as data input. Tens of research works and application of triangular fuzzy regression have dealt with degenerated existing multiplication expressions. This paper highlighted the drawbacks of such expressions and propounded a simple method (named as QKB method). The method is a straightforward method where there is no exaggeration for multiplying two or more TFNs. It respects the trinity-order condition of a TFN where the number without it cannot be considered as a TFN. Besides, it is suitable for known and unknown multiplied TFNs with conserving homogeneity principle such that the resultant of two symmetric TFNs has to be symmetric either, to prove that a proposed new membership function for a TFN (named quantified membership function) has been used. Illustrative examples have shown the soundness of the proposed method and the drawbacks of existing expressions. Furthermore, its expression of multiplication is more efficient than other expression on the needs of computation.
Triangular fuzzy numbers (TFNs),Trinity order condition,homogeneity principle,quantified membership function
http://fomj.qaemiau.ac.ir/article_683799.html
http://fomj.qaemiau.ac.ir/article_683799_68032e7bed585243e48ba12d78266974.pdf
Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
The Zagreb-coindex of Four Operations on Graphs
41
45
EN
Mobina
Ghorbaninejad
Department of Mathematics, Allame Tabarsi Institute, Qaemshahr, Iran
ghorbani325@gmail.com
10.30495/fomj.2021.1931773.1030
In 1972, within a study of the structure-dependency of total π-electron energy (E), it was shown that E depends on the sum of squares of the vertex degrees of the molecular graph (later named first Zagreb index), and thus provides a measure of the branching of the carbon-atom skeleton. Topological indices are found to be very useful in chemistry, biochemistry and nanotechnology in isomer discrimination, structure–property relationship, structure-activity relationship and pharmaceutical drug design. In chemical graph theory, a topological index is a number related to a graph which is structurally invariant. One of the oldest most popular and extremely studied topological indices are well–known Zagreb indices. In a (molecular) graph G, the Zagreb topological index is equal to the sum of squares of the degrees of vertices of G and the Zagreb coindex is defined as the sum of a graph’s vertex degrees which is not adjacent. In this paper, we obtain the Zagreb coindex of four operations on graphs.
Graph,Zagreb–index,F–sum,Zagreb-coindex
http://fomj.qaemiau.ac.ir/article_683880.html
http://fomj.qaemiau.ac.ir/article_683880_bedc36f9d141565eb584e694c585fd4a.pdf
Islamic Azad University, Qaemshahr Branch
Fuzzy Optimization and Modeling Journal
2676-7007
2
2
2021
04
01
A New Approach for Solving Intuitionistic Fuzzy Data Envelopment Analysis Problems
46
57
EN
Francisco Javier
Santos Arteaga
0000-0003-2385-4781
Faculty of Economics and Management, Free University of Bolzano, Bolzano, Italy
fsantosarteaga@unibz.it
Ali
Ebrahimnejad
Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
aemarzoub@gmail.com
Amir
Zabihi
Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
amirzabihi0111@gmail.com
10.30495/fomj.2021.1938179.1033
Data envelopment analysis (DEA) is a mathematical technique based on linear programming applied to evaluate the efficiency of decision-making units dealing with multiple inputs and outputs. In classical DEA models, it is assumed that input and output data are accurate though real-world applications require considering inaccurate and ambiguous data. Moreover, linguistic forms may be intuitionistic in nature rather than fuzzy. We propose a novel approach to solve DEA models characterized by intuitionistic fuzzy data. The model is transformed into a linear programming problem with an intuitionistic fuzzy objective function, and an alphabetical technique is applied to solve it. The proposed approach is easy to implement, involving a lower number of calculations than more computationally demanding techniques introduced in the literature. It also provides a set of ranking results that are significantly correlated with those derived from the implementation of more complex techniques. Its applicability would allow to extend the analysis of intricate evaluation scenarios common to the standard DEA literature into intuitionistic fuzzy environments.
Data envelopment analysis,Intuitionistic Fuzzy Number,Intuitionistic Fuzzy Performance,Accuracy Function
http://fomj.qaemiau.ac.ir/article_684284.html
http://fomj.qaemiau.ac.ir/article_684284_9dfa93d05d5b7f59aa6edfe8bc000df5.pdf