eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-01
9
6
0
10.22111/ijfs.2012.2806
2806
Cover Special Issue vol. 9, no. 6, December 2012
http://ijfs.usb.ac.ir/article_2806_bf0b8dbee5c9d7b98ae157ca9754c9e1.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-27
9
6
1
29
10.22111/ijfs.2012.110
110
مقاله پژوهشی
CREDIBILITY-BASED FUZZY PROGRAMMING MODELS TO
SOLVE THE BUDGET-CONSTRAINED FLEXIBLE
FLOW LINE PROBLEM
Ali Ghodratnama
ghodratn@ut.ac.ir
1
Seyed Ali Torabi
satorabi@ut.ac.ir
2
Raza Tavakkoli-Moghaddam
tavakoli@ut.ac.ir
3
Department of Industrial Engineering, College of Engineering,
University of Tehran, Tehran, Iran
Department of Industrial Engineering, College of Engineering,
University of Tehran, Tehran, Iran
Department of Industrial Engineering, College of En-
gineering, University of Tehran, Tehran, Iran
This paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. Since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzzy) in practice, they are treated as fuzzy variables. Furthermore, to investigate the model behavior and to validate its attribute, we propose three fuzzy programming models based upon credibility measure, namely expected value model, chance-constrained programming model and dependent chance-constrained programming model, in order to transform the original mathematical model into a fuzzy environment. To solve these fuzzy models, a hybrid meta-heuristic algorithm is proposed in which a genetic al- gorithm is designed to compute the number of processors at each stage; and a particle swarm optimization (PSO) algorithm is applied to obtain the op- timal value of tardiness variables. Finally, computational results and some concluding remarks are provided.
http://ijfs.usb.ac.ir/article_110_4cdee35db4712858ef8408c9704bade8.pdf
Budget-constrained
exible
ow lines
Credibility-based fuzzy pro-
gramming
Meta-heuristic
Genetic Algorithm
Particle swarm optimization
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-27
9
6
31
41
10.22111/ijfs.2012.111
111
مقاله پژوهشی
AN ALGEBRAIC STRUCTURE FOR INTUITIONISTIC
FUZZY LOGIC
Esfandiar Eslami
esfandiar.eslami@uk.ac.ir
1
Department of Mathematics, Faculty of Mathematics and Com-
puter, Shahid Bahonar University of Kerman, Kerman, Iran
In this paper we extend the notion of degrees of membership and non-membership of intuitionistic fuzzy sets to lattices and introduce a residuated lattice with appropriate operations to serve as semantics of intuitionistic fuzzy logic. It would be a step forward to find an algebraic counterpart for intuitionistic fuzzy logic. We give the main properties of the operations defined and prove some theorems to demonstrate our goal.
http://ijfs.usb.ac.ir/article_111_92936ce87ae15b80c0c9d17ae0d847e8.pdf
Intuitionistic fuzzy logic
Residuated lattice
Intuitionistic fuzzy
implication
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
43
56
10.22111/ijfs.2012.112
112
مقاله پژوهشی
FUZZY GRADE OF THE COMPLETE HYPERGROUPS
Carmen Angheluta
floryangheluta@yahoo.com
1
Irina Cristea
irinacri@yahoo.co.uk
2
Faculty of Mathematics and Computer Science, University of
Bucharest, Str. Academiei 14, 010014 Bucharest, Romania
Center for Systems and Information Technologies, University of
Nova Gorica, Vipavska 13, SI-5000, Nova Gorica, Slovenia
This paper continues the study of the connection between hyper- groups and fuzzy sets, investigating the length of the sequence of join spaces associated with a hypergroup. The classes of complete hypergroups and of 1-hypergroups are considered and analyzed in this context. Finally, we give a method to construct a nite hypergroup with the strong fuzzy grade equal to a given natural number
http://ijfs.usb.ac.ir/article_112_0ff69d8d879db7c0ac75b78249b3499f.pdf
Complete hypergroup
Join space
Fuzzy set
Fuzzy grade
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
57
67
10.22111/ijfs.2012.113
113
مقاله پژوهشی
DEFUZZIFICATION METHOD FOR RANKING FUZZY
NUMBERS BASED ON CENTER OF GRAVITY
Tofigh Allahviranloo
allahviranloo@yahoo.com
1
Rahim Saneifard
srsaneeifard@yahoo.com
2
Department of Mathematics, Science and Research Branch,
Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic
Azad University, Tehran, Iran
Ranking fuzzy numbers plays a very important role in decision making and some other fuzzy application systems. Many different methods have been proposed to deal with ranking fuzzy numbers. Constructing ranking indexes based on the centroid of fuzzy numbers is an important case. But some weaknesses are found in these indexes. The purpose of this paper is to give a new ranking index to rank various fuzzy numbers effectively. Finally, several numerical examples following the procedure indicate the ranking results to be valid.
http://ijfs.usb.ac.ir/article_113_80aeb7a1e681279f864e912e3a6e965f.pdf
Ranking
Fuzzy numbers
Centroid point
Defuzzification
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
69
85
10.22111/ijfs.2012.114
114
مقاله پژوهشی
A FUZZY DIFFERENCE BASED EDGE DETECTOR
M. A. Nikouei Mahani
nikouei@mahani.info
1
Mohamad Koohi Moghadam
m koohi m@comp.iust.ac.ir
2
Hosein Nezamabadi-pour
nezam@mail.uk.ac.ir
3
Electrical Engineering Department, Shahid Bahonar Univer-
sity of Kerman, Kerman, Iran
School of Computer Engineering, Iran University of
Science and Technology, Tehran, Iran
Electrical Engineering Department, Shahid Bahonar Uni-
versity of Kerman, Kerman, Iran
In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experiments are employed to confirm the robustnessof the proposed algorithm. In the experiments different cases such as normalimages, images corrupted by Gaussian noise, and uneven lightening imagesare involved. The results obtained are compared with some famous algorithmssuch as Canny and Sobel operators, a competitive fuzzy edge detector, and astatistical based edge detector. The visual and quantitative comparisons showthe effectiveness of the proposed algorithm even for those images that werecorrupted by strong noise.
http://ijfs.usb.ac.ir/article_114_04f71f0b2f0662f7763880565a251dae.pdf
Edge detection
Fuzzy edge detection
Dynamic membership function
Fuzzy dierence
Noisy images
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
87
99
10.22111/ijfs.2012.115
115
مقاله پژوهشی
SYMMETRIC TRIANGULAR AND INTERVAL
APPROXIMATIONS OF FUZZY SOLUTION TO
LINEAR FREDHOLM FUZZY INTEGRAL
EQUATIONS OF THE SECOND KIND
Majid Alavi
M-alavi@Iau-arak.ac.ir
1
Babak Asady
B-asay@Iau-arak.ac.ir
2
Department of Mathematics, Islamic Azad University, Arak Branch,
Arak, Iran
Department of Mathematics, Islamic Azad University, Arak Branch,
Arak, Iran
In this paper a linear Fuzzy Fredholm Integral Equation(FFIE) with arbitrary Fuzzy Function input and symmetric triangular (Fuzzy Interval) output is considered. For each variable, output is the nearest triangular fuzzy number (fuzzy interval) to the exact fuzzy solution of (FFIE).
http://ijfs.usb.ac.ir/article_115_4867dc5fc41055bc015b22cd768c5f10.pdf
Fuzzy number
Expected interval
Fuzzy integral equations
Symmetric
fuzzy number
Nystrom method
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
101
111
10.22111/ijfs.2012.120
120
مقاله پژوهشی
THE RELATIONSHIP BETWEEN L-FUZZY PROXIMITIES AND
L-FUZZY QUASI-UNIFORMITIES
Eun-Seok Kim
manmunje@hanmail.net
1
Seung-Ho Ahn
shahn@chonnam.ac.kr
2
Dae Heui Park
dhpark3331@chonnam.ac.kr
3
Department of Mathematics, Chonnam National University, 300 Yongbong-
dong, Bukgu, 500-757, Gwangju, Korea
Department of Mathematics, Chonnam National University, 300 Yongbong-
dong, Bukgu, 500-757, GwangJu, Korea
Department of Mathematics, Chonnam National University, 300 Yongbong-
dong, Bukgu, 500-757, GwangJu, Korea
In this paper, we investigate the L-fuzzy proximities and the relationships betweenL-fuzzy topologies, L-fuzzy topogenous order and L-fuzzy uniformity. First, we show that the category of-fuzzy topological spaces can be embedded in the category of L-fuzzy quasi-proximity spaces as a coreective full subcategory. Second, we show that the category of L -fuzzy proximity spaces is isomorphic to the category of L-fuzzy topogenous order spaces. Finally,we obtain that the category of L-fuzzy proximity spaces can be embeddedin the category of L-fuzzy uniform spaces as a bireective full subcategory.
http://ijfs.usb.ac.ir/article_120_e9a1f2dafb8bbda298f95ab61533e4c2.pdf
L-Fuzzy topology
L-fuzzy proximity
L-fuzzy uniformity
L-fuzzy
topogenous order
Fuzzy remote neighborhood systems
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
113
122
10.22111/ijfs.2012.121
121
مقاله پژوهشی
Uniquely Remotal Sets in $c_0$-sums and $ell^infty$-sums of Fuzzy Normed Spaces
Alireza Kamel Mirmostafaee
mirmostafaei@ferdowsi.um.ac.ir
1
Madjid Mirzavaziri
mirzavaziri@gmail.com
2
Center of Excellence in Analysis on Algebraic Struc-
tures, Department of Pure Mathematics, Ferdowsi University of Mashhad, P. O. Box
1159, Mashhad 91775, Mashhad, Iran
Center of Excellence in Analysis on Algebraic Structures, De-
partment of Pure Mathematics, Ferdowsi University of Mashhad, P. O. Box 1159, Mash-
had 91775, Mashhad, Iran
Let $(X, N)$ be a fuzzy normed space and $A$ be a fuzzy boundedsubset of $X$. We define fuzzy $ell^infty$-sums and fuzzy $c_0$-sums offuzzy normed spaces. Then we will show that in these spaces, all fuzzyuniquely remotal sets are singletons.
http://ijfs.usb.ac.ir/article_121_ff6e9553bb02f301be1760cab42930a1.pdf
Fuzzy normed spaces
Fuzzy remotal set
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-02
9
6
123
133
10.22111/ijfs.2012.124
124
مقاله پژوهشی
(IC)LM-FUZZY TOPOLOGICAL SPACES
Hai-Yang Li
fplihiayang@126.com
1
School of Science, Xi'an Polytechnic University, Xi'an 710048, P. R.
China
The aim of the present paper is to define and study (IC)$LM$-fuzzytopological spaces, a generalization of (weakly) induced $LM$-fuzzytopological spaces. We discuss the basic properties of(IC)$LM$-fuzzy topological spaces, and introduce the notions ofinterior (IC)-fication and exterior (IC)-fication of $LM$-fuzzytopologies and prove that {bf ICLM-FTop} (the category of(IC)$LM$-fuzzy topological spaces) is an isomorphism-closed fullproper subcategory of {bf LM-FTop} (the category of $LM$-fuzzytopological spaces) and {bf ICLM-FTop} is a simultaneouslybireflective and bicoreflective full subcategory of {bf LM-FTop}.
http://ijfs.usb.ac.ir/article_124_a929db0f489a56ad82899d80d76f5f06.pdf
LM-fuzzy topology
(IC) LM-fuzzy topological spaces
(IC)-fication
of LM-fuzzy topology
Category
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-12-01
9
6
137
145
10.22111/ijfs.2012.2807
2807
Persian-translation Vol.9, No.6
http://ijfs.usb.ac.ir/article_2807_82664d9575be6d31f502231085f96bf9.pdf