Cover Special Issue vol. 8, no. 4, October 2011
text
article
2011
eng
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
0
http://ijfs.usb.ac.ir/article_2868_3f83c7d9389a4164783e5336fe598543.pdf
dx.doi.org/10.22111/ijfs.2011.2868
SOME PROPERTIES FOR FUZZY CHANCE CONSTRAINED
PROGRAMMING
Xiaohu
Yang
Department of Statistics, Xi'an University of Finance and Economics,
Xi'an 710061, China
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
1
8
http://ijfs.usb.ac.ir/article_305_6fb6b2d1b824c72a0c944ba1a2867828.pdf
dx.doi.org/10.22111/ijfs.2011.305
ALGORITHMS FOR BIOBJECTIVE SHORTEST PATH
PROBLEMS IN FUZZY NETWORKS
Iraj
Mahdavi
Department of Industrial Engineering, Mazandaran University of Sci-
ence & Technology, Babol, Iran
author
Nezam
Mahdavi-Amiri
Faculty of Mathematical Sciences, Sharif University of Tech-
nology, Tehran, Iran
author
Shahrbanoo
Nejati
Department of Industrial Engineering, Mazandaran University
of Science & Technology, Babol, Iran
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
9
37
http://ijfs.usb.ac.ir/article_306_645249d97ea17b67c4eb5772a11928ac.pdf
dx.doi.org/10.22111/ijfs.2011.306
A FUZZY MINIMUM RISK MODEL FOR THE RAILWAY
TRANSPORTATION PLANNING PROBLEM
Lixing
Yang
State Key Laboratory of Rail Traffic Control and Safety, Beijing
Jiaotong University, Beijing 100044, China
author
Xiang
Li
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
author
Ziyou
Gao
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
author
Keping
Li
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong
University, Beijing 100044, China
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
39
60
http://ijfs.usb.ac.ir/article_307_3d5c42e3f0fbf960235d85616888b3fc.pdf
dx.doi.org/10.22111/ijfs.2011.307
MEAN-ABSOLUTE DEVIATION PORTFOLIO SELECTION
MODEL WITH FUZZY RETURNS
Zhongfeng
Qin
School of Economics and Management, Beihang University, Beijing
100191, China
author
Meilin
Wen
School of Reliability and Systems Engineering, Beihang University,
Beijing 100191, China
author
Changchao
Gu
Sinopec Management Institute, Beijing 100012, China
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
61
75
http://ijfs.usb.ac.ir/article_308_3b4ec0110e6e5007d107918ec346e5a6.pdf
dx.doi.org/10.22111/ijfs.2011.308
FUZZY TRAIN ENERGY CONSUMPTION MINIMIZATION
MODEL AND ALGORITHM
Xiang
Li
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiao-
tong University, Beijing 100044, China
author
Dan
Ralescu
Department of Mathematical Sciences, University of Cincinnati, Cincin-
nati, Ohio 45221, USA
author
Tao
Tang
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiao-
tong University, Beijing 100044, China
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
77
91
http://ijfs.usb.ac.ir/article_309_b33ac36fdf8e3fc3c689b9438a056dfa.pdf
dx.doi.org/10.22111/ijfs.2011.309
FLUENCE MAP OPTIMIZATION IN INTENSITY MODULATED
RADIATION THERAPY FOR FUZZY TARGET DOSE
Alireza
Fakharzadeh Jahromi
Shiraz University of Technology, Shiraz, Fars, Iran
author
Omolbanin
Bozorg
Shiraz University of Technology, Shiraz, Fars, Iran
author
Hamidreza
Maleki
Shiraz University of Technology, Shiraz, Fars, Iran
author
Mohamad Amin
Mosleh-Shirazi
Shiraz University of Medical Sciences, Shiraz, Fars,
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
93
105
http://ijfs.usb.ac.ir/article_310_624d131dd630762401d6a0a4997854fa.pdf
dx.doi.org/10.22111/ijfs.2011.310
COALITIONAL GAME WITH FUZZY PAYOFFS AND
CREDIBILISTIC SHAPLEY VALUE
Jinwu
Gao
Uncertain Systems Lab, School of Information, Renmin University of
China, Beijing 100872, China
author
Q.
Zhang
Uncertain Systems Lab, School of Information, Renmin University of
China, Beijing 100872, China
author
P.
Shen
Uncertain Systems Lab, School of Information, Renmin University of China,
Beijing 100872, China
author
text
article
2011
eng
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.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
107
117
http://ijfs.usb.ac.ir/article_311_ec8eadf2c503f1494486ac8555956b9a.pdf
dx.doi.org/10.22111/ijfs.2011.311
Persian-translation vol. 8, no. 4, October 2011
text
article
2011
eng
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
8
v.
4
no.
2011
121
127
http://ijfs.usb.ac.ir/article_2869_0ffa9f8030e868147b8d43909fd9e0de.pdf
dx.doi.org/10.22111/ijfs.2011.2869