eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-29
8
4
0
10.22111/ijfs.2011.2868
2868
Cover Special Issue vol. 8, no. 4, October 2011
http://ijfs.usb.ac.ir/article_2868_3f83c7d9389a4164783e5336fe598543.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-06
8
4
1
8
10.22111/ijfs.2011.305
305
مقاله پژوهشی
SOME PROPERTIES FOR FUZZY CHANCE CONSTRAINED
PROGRAMMING
Xiaohu Yang
yxh12@163.com
1
Department of Statistics, Xi'an University of Finance and Economics,
Xi'an 710061, China
Convexity theory and duality theory are important issues in math-
ematical programming. Within the framework of credibility theory, this paper
rst introduces the concept of convex fuzzy variables and some basic criteria.
Furthermore, a convexity theorem for fuzzy chance constrained programming
is proved by adding some convexity conditions on the objective and constraint
functions. Finally, a duality theorem for fuzzy linear chance constrained pro-
gramming is proved.
http://ijfs.usb.ac.ir/article_305_6fb6b2d1b824c72a0c944ba1a2867828.pdf
Convexity theorem
Duality theorem
Fuzzy variable
Chance con-
strained programming
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
9
37
10.22111/ijfs.2011.306
306
مقاله پژوهشی
ALGORITHMS FOR BIOBJECTIVE SHORTEST PATH
PROBLEMS IN FUZZY NETWORKS
Iraj Mahdavi
irajarash@rediffmail.com
1
Nezam Mahdavi-Amiri
nezamm@sharif.edu
2
Shahrbanoo Nejati
nejati sh@yahoo.com
3
Department of Industrial Engineering, Mazandaran University of Sci-
ence & Technology, Babol, Iran
Faculty of Mathematical Sciences, Sharif University of Tech-
nology, Tehran, Iran
Department of Industrial Engineering, Mazandaran University
of Science & Technology, Babol, Iran
We consider biobjective shortest path problems in networks with
fuzzy arc lengths. Considering the available studies for single objective shortest
path problems in fuzzy networks, using a distance function for comparison of
fuzzy numbers, we propose three approaches for solving the biobjective prob-
lems. The rst and second approaches are extensions of the labeling method to
solve the single objective problem and the third approach is based on dynamic
programming. The labeling methods usually producing several nondominated
paths, we propose a fuzzy number ranking method to determine a fuzzy short-
est path. Illustrative examples are worked out to show the eectiveness of our
algorithms.
http://ijfs.usb.ac.ir/article_306_645249d97ea17b67c4eb5772a11928ac.pdf
Biobjective shortest path
Fuzzy network
Labeling method
Dynamic
programming
Fuzzy ranking methods
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
39
60
10.22111/ijfs.2011.307
307
مقاله پژوهشی
A FUZZY MINIMUM RISK MODEL FOR THE RAILWAY
TRANSPORTATION PLANNING PROBLEM
Lixing Yang
lxyang@bjtu.edu.cn
1
Xiang Li
xiang-li04@tsinghua.edu.cn
2
Ziyou Gao
gaoziyou@jtys.bjtu.edu.cn
3
Keping Li
likeping@jtys.bjtu.edu.cn
4
State Key Laboratory of Rail Traffic Control and Safety, Beijing
Jiaotong University, Beijing 100044, China
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
The railway transportation planning under the fuzzy environment
is investigated in this paper. As a main result, a new modeling method, called
minimum risk chance-constrained model, is presented based on the credibility
measure. For the convenience ofs olving the mathematical model, the crisp
equivalents ofc hance functions are analyzed under the condition that the
involved fuzzy parameters are trapezoidal fuzzy variables. An approximate
model is also constructed for the problem based on an improved discretization
method for fuzzy variables and the relevant convergence theorems. To
obtain an approximate solution, a tabu search algorithm is designed for the
presented model. Finally, some numerical experiments are performed to show
the applications ofthe model and the algorithm.
http://ijfs.usb.ac.ir/article_307_3d5c42e3f0fbf960235d85616888b3fc.pdf
Minimum risk model
Railway transportation planning
Credibility
measure
Discretization method
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
61
75
10.22111/ijfs.2011.308
308
مقاله پژوهشی
MEAN-ABSOLUTE DEVIATION PORTFOLIO SELECTION
MODEL WITH FUZZY RETURNS
Zhongfeng Qin
qin@buaa.edu.cn, qzf05@mails.thu.edu.cn
1
Meilin Wen
wenmeilin@buaa.edu.cn
2
Changchao Gu
guchangchao@gamil.com
3
School of Economics and Management, Beihang University, Beijing
100191, China
School of Reliability and Systems Engineering, Beihang University,
Beijing 100191, China
Sinopec Management Institute, Beijing 100012, China
In this paper, we consider portfolio selection problem in which
security returns are regarded as fuzzy variables rather than random variables.
We first introduce a concept of absolute deviation for fuzzy variables and
prove some useful properties, which imply that absolute deviation may be
used to measure risk well. Then we propose two mean-absolute deviation
models by defining risk as absolute deviation to search for optimal portfolios.
Furthermore, we design a hybrid intelligent algorithm by integrating genetic
algorithm and fuzzy simulation to solve the proposed models. Finally, we
illustrate this approach with two numerical examples.
http://ijfs.usb.ac.ir/article_308_3b4ec0110e6e5007d107918ec346e5a6.pdf
Uncertainty modelling
Fuzzy variable
Fuzzy portfolio selection
Credibility theory
Hybrid intelligent algorithm
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
77
91
10.22111/ijfs.2011.309
309
مقاله پژوهشی
FUZZY TRAIN ENERGY CONSUMPTION MINIMIZATION
MODEL AND ALGORITHM
Xiang Li
xiang-li04@mail.tsinghua.edu.cn
1
Dan Ralescu
ralescd@uc.edu
2
Tao Tang
ttang@bjtu.edu.cn
3
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiao-
tong University, Beijing 100044, China
Department of Mathematical Sciences, University of Cincinnati, Cincin-
nati, Ohio 45221, USA
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiao-
tong University, Beijing 100044, China
Train energy saving problem investigates how to control train's
velocity such that the quantity of energy consumption is minimized and some
system constraints are satis ed. On the assumption that the train's weights
on different links are estimated by fuzzy variables when making the train
scheduling strategy, we study the fuzzy train energy saving problem. First, we
propose a fuzzy energy consumption minimization model, which minimizes the
average value and entropy of the fuzzy energy consumption under the maximal
allowable velocity constraint and traversing time constraint. Furthermore, we
analyze the properties of the optimal solution, and then design an iterative
algorithm based on the Karush-Kuhn-Tucker conditions. Finally, we illustrate
a numerical example to show the effectiveness of the proposed model and
algorithm.
http://ijfs.usb.ac.ir/article_309_b33ac36fdf8e3fc3c689b9438a056dfa.pdf
Energy consumption
Train scheduling
Karush-Kuhn-Tucker condi-
tions
Fuzzy variable
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
93
105
10.22111/ijfs.2011.310
310
مقاله پژوهشی
FLUENCE MAP OPTIMIZATION IN INTENSITY MODULATED
RADIATION THERAPY FOR FUZZY TARGET DOSE
Alireza Fakharzadeh Jahromi
a_ fakharzadeh@sutech.ac.ir
1
Omolbanin Bozorg
o.bozorg@gmail.com
2
Hamidreza Maleki
maleki@sutech.ac.ir
3
Mohamad Amin Mosleh-Shirazi
mosleh_amin@hotmail.com
4
Shiraz University of Technology, Shiraz, Fars, Iran
Shiraz University of Technology, Shiraz, Fars, Iran
Shiraz University of Technology, Shiraz, Fars, Iran
Shiraz University of Medical Sciences, Shiraz, Fars,
Although many methods exist for intensity modulated radiotherapy (IMRT) fluence map optimization for crisp data, based on clinical practice, some of the involved parameters are fuzzy. In this paper, the best fluence maps for an IMRT procedure were identifed as a solution of an optimization problem with a quadratic objective function, where the prescribed target dose vector was fuzzy. First, a defuzzyingprocedure was introduced to change the fuzzy model of the problem into an equivalent non-fuzzy one. Since the solution set was nonconvex, the optimal solution was then obtained by performing a projection operation in applying the gradient method. Numerical simulations for two typical clinical cases (for prostate and head-and-neck cancers, each for two patients) are given.
http://ijfs.usb.ac.ir/article_310_624d131dd630762401d6a0a4997854fa.pdf
IMRT
Singed distance
Triangular fuzzy number
Gradient method
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-07
8
4
107
117
10.22111/ijfs.2011.311
311
مقاله پژوهشی
COALITIONAL GAME WITH FUZZY PAYOFFS AND
CREDIBILISTIC SHAPLEY VALUE
Jinwu Gao
jgao@ruc.edu.cn
1
Q. Zhang
zqw2002@163.com
2
P. Shen
shenpuchen@163.com
3
Uncertain Systems Lab, School of Information, Renmin University of
China, Beijing 100872, China
Uncertain Systems Lab, School of Information, Renmin University of
China, Beijing 100872, China
Uncertain Systems Lab, School of Information, Renmin University of China,
Beijing 100872, China
Coalitional game deals with situations that involve cooperations among players, and there are different solution concepts such as the core,the Shapley value and the kernel. In many situations, there is no way to predict the payoff functions except for the expert experiencesand subjective intuitions, which leads to the coalitional game with fuzzy payoffs. Within the framework of credibility theory, this paper employstwo credibilistic approaches to define the behaviors of players under fuzzy situations. Correspondingly, two variations of Shapley value areproposed as the solutions of the coalitional game with fuzzy payoffs. Meanwhile, some characterizations of the credibilistic Shapley valueare investigated. Finally, an example is provided for illustrating the usefulness of the theory developed in this paper.
http://ijfs.usb.ac.ir/article_311_ec8eadf2c503f1494486ac8555956b9a.pdf
Coalitional game
Shapley value
Fuzzy variable
Credibility measure
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-29
8
4
121
127
10.22111/ijfs.2011.2869
2869
Persian-translation vol. 8, no. 4, October 2011
http://ijfs.usb.ac.ir/article_2869_0ffa9f8030e868147b8d43909fd9e0de.pdf