دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
Design a Discriminative Learning Model to Improve Bus Routes of Bus Transit Network
1
18
FA
mjahanshahi@iauctb.ac.ir
Y
N
N
N
Design a Bus Transit Network is an important problem of the Urban Management. There are a large number of variables that must be considered to design a bus transit network. These variables are used to reach a set of goals such as accessibility, maximum coverage, reduction of waiting time and decrease operational costs and number of transfer between line stops. Design a Bus Transit Network is NP-hard problem. This problem doesn't have optimal solution in large scale. The general way to design Bus Transit Network is as follows: Search space of feasible solutions are reduced then final network is constructed by notice to urban priorities. In this paper, we proposed a new method to design a Bus Transit Network. Our approach is a Statistical learning method. It extracts knowledge of human experts from existing Bus Transit Networks. Then this knowledge is applied to reduce search space and make a Bus Transit Network. The learned model of our approach is constructed by several statistical learning method and their hybrids. In this paper, we applied Naïve Bayesian, two regression based methods and hybrid version of them to build model. Evaluation of the learned model is based on Accuracy, False Positive and True Positive criteria. The values of these criteria show high confidence of our approach. In this paper, we applied Tehran Bus Transit Network as our data set.
Regression, Naïve Bayesian, Bus Transit Network (BTN), Bus Transit Network Design Problem (BTNDP).
http://jamlu.liau.ac.ir/article-1-1307-en.html
http://jamlu.liau.ac.ir/article-1-1307-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
An Efficient Algorithm for the Extended Trust Region Subproblem with Two Linear Constraints
19
33
FA
N
salahim@guilan.ac.ir
Y
Trust region subproblem (TRS), which is the problem of minimizing a quadratic function over a ball, plays a key role in solving unconstrained nonlinear optimization problems. Though TRS is not necessarily convex, there are efficient algorithms to solve it, particularly in large scale. Recently, extensions of TRS with extra linear constraints have received attention of several researchers. It has been shown that in the case where the linear constraints do not intersect within the ball, the optimal solution of the extended problem can be computed via solving a conic optimization problem. However, solving large-scale or even medium scale conic optimization problems are not practicable. In this paper, the extended trust region subproblem with two linear constraints without any assumptions on the constraints is considered. The latest algorithms for solving TRS and computing its local non-global minimizer, that solve the problem via a generalized eigenvalue problem, are used to solve the extended trust region subproblem. Finally, the efficiency of the proposed algorithm is evaluated on several randomly generated instances
Extend Trust Region Subproblem, Generalized Eigenvalue Problem, Global Optimization.
http://jamlu.liau.ac.ir/article-1-1333-en.html
http://jamlu.liau.ac.ir/article-1-1333-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
Optimization Parallel Algorithm Scheduling by Genetic Algorithm
35
52
FA
N
Ah_refahi@liau.ac.ir
Y
N
In scheduling, a set of machines in parallel is a setting that is important, from both the theoretical and practical points of view. From the theoretical viewpoint, it is a generalization of the single machine scheduling problem. From the practical point of view the occurrence of resources in parallel is common in real-world. When machines are computers, a parallel program can be conceived as a set of parallel components (tasks) which can be executed according to some precedence relationship. This paper shows the problem of allocating a number of non-identical tasks in a multi-processor or multicomputer system. The model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are non-preemptive.
Genetic Algorithm, Parallel Algorithm, Task Graph, Task Scheduling
http://jamlu.liau.ac.ir/article-1-1346-en.html
http://jamlu.liau.ac.ir/article-1-1346-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
Optimum Fuzzy Non-parametric Predictive Inference for Single Acceptance Sampling
53
68
FA
N
sadeghpour@um.ac.ir
Y
N
N
Acceptance sampling is one of the main parts of the statistical quality control. It is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling procedures can be used in an acceptance control program to reach better quality with lower expenses, improvement of the control and the increase of efficiency. The aims of this paper, studying acceptance sampling based on non-parametric predictive inference in a fuzzy environment. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. Especially in production environments, it may not be easy to define the parameters number of conforming items and the size of the samples crisp values. In these cases, these parameters can be expressed by linguistic variables. The fuzzy set theory can be used successfully to cope the vagueness in these linguistic expressions for acceptance sampling based on non-parametric predictive inference. In other words, the aim of this paper is present a new method titled fuzzy non-parametric predictive inference for single acceptance sampling plan
Fuzzy Numbers, Non-Parametric Predictive Inference, Acceptance Sampling
http://jamlu.liau.ac.ir/article-1-1376-en.html
http://jamlu.liau.ac.ir/article-1-1376-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
The Optimal Algorithms for Backup Undesirable 2-Center Location Models on Tree Graphs
69
83
FA
N
alizadeh@sut.ac.ir
Y
N
In this paper, we investigate the backup undesirable -center location models on tree graphs. The aim is to obtain the best locations on the vertex set of the underlying tree for establishing two undesirable servers so that the expected value of the closest distance from the existing customers to the functioning facilities is maximized under the assumption that any facility may fail with a given probability and in this case the other active server must serve all the customers. The exact combinatorial algorithms with and time complexities are developed for obtaining the optimal solutions of two certain models, where is the number of the vertices in the given tree graph.
Combinatorial Optimization, Facility Location, Backup Undesirable Center, Time Complexity.
http://jamlu.liau.ac.ir/article-1-1377-en.html
http://jamlu.liau.ac.ir/article-1-1377-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
A Filtered Nonmonotone Approach for Solving Nonlinear Systems of Equations
85
99
FA
N
peyghami@kntu.ac.ir
Y
In this paper, a new approach is presented for solving nonlinear systems of equations in which a derivative-free nonmonotone strategy is employed. Besides, the new approach is equipped with a filter technique. Using this concept, we store some trial points that are probably ignored by some other line search methods. The new algorithm utilizes the information of existing points in the filter in order to accept the new point. This causes a fast convergence rate. A specific nonmonotone technique is also used in the structure of the new approach which allows the algorithm to enjoy the nonmonotonicity from scratch. Under some standard assumptions, the global convergence property is established. Numerical results on some test problems show the efficiency of the proposed algorithm compared with some other existing methods in the literature
Systems of Nonlinear Equations, Filter Technique, Nonmonotone Line Search Method, Global Convergence
http://jamlu.liau.ac.ir/article-1-1399-en.html
http://jamlu.liau.ac.ir/article-1-1399-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
A Linear Algorithm for Finding Core of Weighted Interval Trees
101
111
FA
Y
fathali@shahroodut.ac.ir
N
In this paper we consider the problem of finding a core of weighted interval trees. A core of an interval graph is a path contains some intervals of graph so that the sum of distances from all intervals to this path is minimized. We show that intervals on core of a tree should be maximal, then a linear time algorithm is presented to find the core of interval trees
Interval Graph, Core of Tree, Location Problem
http://jamlu.liau.ac.ir/article-1-1412-en.html
http://jamlu.liau.ac.ir/article-1-1412-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
13
2
2016
8
1
Two Statistical Tests for Outlier Identification in Non-Parametric Performance Measurement
113
121
FA
mfsiavash@gmail.com
Y
N
N
In data envelopment analysis the use of peer set to assess individual or best practice performance, detecting outliers is critical for achieving accurate results. In these deterministic frontier models, statistical tests are now mostly available. This paper deals with two statistical tests for detecting outliers in data envelopment analysis. In the presented methods, each observation is deleted from the sample once and the resulting DEA model is solved, leading to a distribution of efficiency estimates; before and after elimination. Based on the achieved distribution, two statistical tests are then designed to identify the potential outlier(s). We illustrate the method through a real data set. The method could be used in a first step before using any frontier estimation
Data Envelopment Analysis (DEA), Outlier, Efficiency, Chebyshev’s Inequality test, Cook Statistics
http://jamlu.liau.ac.ir/article-1-1413-en.html
http://jamlu.liau.ac.ir/article-1-1413-en.pdf