دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
A new Group Voting Analytical Hierarchy Process Method
1
13
FA
Mehdi
Soltanifar
Islamic Azad University, Semnan Brancu
soltanifar@khayam.ut.ac.ir
Y
Selecting the appropriate options in order to use available resources efficiently has always been considered by managers and as a result there are different attitudes to make maximum use of these resources. Restriction of capital, labor, energy, competitive market, etc. has led managers to find an optimal solution. One of the most widely used of these methods is Analytical Hierarchy Process which uses paired comparisons between options and also criteria to prioritize them. On the other hand in the real world, decision-makers’ views do not always have the same significance (importance) levels. Due to the use of pair wise comparison matrices Analytical Hierarchy Process is time consuming. In this paper a new method for Group Analytical Hierarchy Process with unequal decision makers by using a voting model is provided. Superior of this approach is compared to the previous ones by a numerical example.
Analytical Hierarchy Process, Group Decision, Voting.
http://jamlu.liau.ac.ir/article-1-1434-en.html
http://jamlu.liau.ac.ir/article-1-1434-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
A multi-period and three-echelon supply chain network design for perishable agricultural products using meta-heuristic algorithms
15
34
FA
Armin
Cheraghalipour
University of Science and Technology of Mazandaran
bmtarmin@yahoo.com
N
Mohammad Mahdi
Paydar
Babol University of Technology
paydar@nit.ac.ir
Y
Mostafa
Hajiaghaei-Keshteli
University of Science and Technology of Mazandaran
mostafahaji@mazust.ac.ir
N
A considerable amount of perishable products especially in the food and agriculture is corrupted annually due to the lack of effective mechanism in the supply chain. So, in this study, we tried to improve these unfavorable conditions by designing an efficient supply chain network minimizing costs for perishable products. Due to lack of adequate researches in the field of perishable supply chain network design, this study can be considered as one of the basic research in this field. In order to analysis and verify the proposed model, a case study in Mazandaran province has been applied. Since the proposed model on a large scale problem is NP-hard, therefore, the meta-heuristic algorithms are developed to solve the problem. It should be noted that in order to compare the performance of these algorithms on the small size problems, the branch and bound method via Lingo software is used. Finally, conclusions and suggestions for future research are presented.
Perishable products supply chain, Metaheuristic, Linear programming, branch and bound method.
http://jamlu.liau.ac.ir/article-1-1342-en.html
http://jamlu.liau.ac.ir/article-1-1342-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
Robustness of DEA models to identify worst-practice DMUs
35
53
FA
Aliasghar
Arabmaldar
university of sistan and baluchestan
Aliasghar.Arabmaldar@gmail.com
Y
faranak
hosseinzadeh saljooghi
university of sistan and baluchestan
f_h_saljooghi@yahoo.com
N
An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices to finding worst-practice DMUs. Indeed classical DEA models evaluate each DMUs compared to the most effective DMU. Since in this way the relative efficiency is calculated, therefore at least one of the DMUs are located on the efficiency frontier. In comparison to classical DEA models, there are other DEA models which evaluate DMUs based on unfavorable scenario and by making the inefficiency frontier, identify the DMUs with worst-practice performance. The efficient DMUs obtained from the original DEA construct an efficient (best-practice) frontier. In this paper, by using of robust optimization approaches, we proposed two models to evaluate DMUs in the worst-practice sense and our aim is to obtain DMUs with worst-practice performance in problems that faced with uncertainty in data. Also to ranking the DMUs with worst-practice we use the super-efficiency concept and called it super-inefficiency. By using of two numerical example we demonstrate the capability of proposed models in presentation of reliable ranking and finding the worst-practice DMUs.
Data Envelopment Analysis, Robust optimization, Uncertainty, Ranking, Worst-Practice.
http://jamlu.liau.ac.ir/article-1-1297-en.html
http://jamlu.liau.ac.ir/article-1-1297-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
Implementation of indirect impact factor related to inputs and outputs in the performance evaluation of decision making units in DEA
55
67
FA
H.
Siaby
hamidsiaby@yahoo.com
N
M.
Rodtami malkhalifeh
mohsen_rostamy@yahoo.com
Y
F.
Hosseinzadeh lotfi
farhad@hosseinzadeh.ir
N
M.H
behzadi
behzadi@srbiau.ac.ir
N
Data Envelopment Analysis (DEA) is a non-parametric method for estimation of production function. In DEA, each decision making unit (DMU) has a number of input and output and deals with performance evaluation of DMUs using frontier efficiency. Each one of the inputs and outputs plays a basic role in the performance evaluation of DMU which they can be named as direct impact factor. Inputs and outputs of the DMU have, also, an indirect impact on the performance evaluation of DMUs, which one of blind spots of DEA models is not in consideration of these factors which they can be known as indirect impact factor. Due to their essence and nature, indirect impact factors have influence on the efficiency negatively, and these factors cannot be taken into consideration as input or output or, controllable input or outputs. Recognition of indirect impact factors plays a remarkable role in the performance evaluation and ranking of DMUs. Therefore, some methods have been presented in this paper for performance evaluation and ranking of DMUs based on indirect impact factors.
Data envelopment analysis, indirect impact factors, ranking.
http://jamlu.liau.ac.ir/article-1-1538-en.html
http://jamlu.liau.ac.ir/article-1-1538-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
A new heuristic algorithm for total covering location problem
69
88
FA
Sattar
Rajabpour sanati
Iran University of Science and Technology
sanati.sattar@gmail.com
N
Ali
Naimi Sadigh
Iranian Research Institute for Information Science and Technology (IRANDOC)
naimi@irandoc.ac.ir
Y
Set covering problem has many applications such as emergency systems, retailers’ facilities, hospitals, radar devices, and military logistics, and it is considered as Np-Hard problems. The goal of set covering problem is to find a subset such that :::::::::union::::::::: of the subset members covered the whole set. In this paper, we present a new heuristic algorithm to solve the set covering problem. In the heuristic algorithm, the amounts of improvement are calculated for any of vertices in the graph. Based on the improvement we consider vertices in the subset. The amounts of improvement updated in each iteration to find near optimal solution. A simulated annealing algorithm, which its parameters tuned with Taguchi method, is presented to compare with our suggested heuristic algorithm. The computational results show that the heuristic algorithm works better than the simulated annealing algorithm in both quality of solution, and time view.
Covering problem, Heuristic algorithm, Simulated annealing algorithm, Taguchi method
http://jamlu.liau.ac.ir/article-1-1234-en.html
http://jamlu.liau.ac.ir/article-1-1234-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
Solving estimating equation of regression models with random measurement error on independent variable by optimization approach
89
98
FA
M.
Babanezhad
Golestan University
mbaba222@yahoo.com
Y
Measurements of some variables in statistical analysis are often encountered with random errors. Therefore, investigating of the effects of these errors seems to be important. This event in regression analysis seems to be more necessary. Because the aim of the fitting a regression model is estimating the effect of an independent variable on a response variable. Then measurements of an independent variable in a regression model are subject to random error, this may affect the parameter estimating processes. In this article, we first investigate how random errors occur on the measurements of a random variable. Then we show that exist such an error on the measurements of the independent variable has an impact on the estimating of the parameters, such that it makes impossible to directly solve the estimating equations for the estimating of the regression model parameters. We also show with an optimization procedure by solving the estimating equations the estimation of model parameters can be achieved. Finally, we test the results of the optimization procedure on two practical examples, and we illustrate the effects of ignoring random errors in estimating model parameters in these two examples.
Random errors, Linear and non-linear regression models, Estimating equations, Optimization.
http://jamlu.liau.ac.ir/article-1-1387-en.html
http://jamlu.liau.ac.ir/article-1-1387-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
Presenting a school bus routing problem with consideration of students outsourcing possibility
99
115
FA
Parsa
Parvasi
Khaje Nasir university of technology
parsa.parvasi@gmail.com
N
Amirhosein
Patoghi
Khaje Nasir university of technology
amirhpa.ah@gmail.com
N
Milad
Rahimi Moghadam
Khaje Nasir university of technology
milad.mrm@gmail.com
N
Emad
Roghanian
Khaje Nasir university of technology
e_roghanian@kntu.ac.ir
Y
Current studies regarding to school bus routing problem basically are about travel time and cost of travel minimization. In this paper we pay more attention to the challenges of Transportation Company in getting students to their school in a way that maximize the company profit as well as minimize the cost of students assignment. In this study for the first time the transportation company is allowed to pay a fine to students in order to not serving them. In the investigated school bus routing problem, the following will be considered simultaneously:
Enabling potential stations(location)
Determining which students to be assigned to which stations and which students to be paid by company for not being served(allocation)
Determining routs among stations so that the total traveled distance be minimized(routing)
A single objective mix integer programming of this problem is developed. Finally, an exact approach and a metaheuristic procedure is proposed for solving the problem. The results of this two approaches are studied in 5 generated samples and the results indicate good performance of metaheuristic procedure.
location, routing, students assignment, mix integer programming, tabu search
http://jamlu.liau.ac.ir/article-1-1199-en.html
http://jamlu.liau.ac.ir/article-1-1199-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
3
2017
10
1
Centralized Resource Allocation based on the Value Efficiency in DEA and DEA-R
117
130
FA
Mohammad reza
Mozaffari
Islamic Azad University, Shiraz Brancu
mozaffari854@yahoo.com
Y
In this article, centralized resource allocation (CRA) models based on the value efficiency in DEA and DEA-R are recommended. In general, if the input and output data of decision-making units are available, DEA models provide targets of units on the efficiency frontier in addition to the efficiency of units. However, if only a ratio of the input data to output data, or vice versa, is available, DEA models cannot determine the efficiency and target of units. In order to overcome this problem, DEA-R models are utilized. With a linear programming problem, centralized resource allocation models can achieve the projection of all decision-making units on the efficiency frontier. Therefore, in the present article the projection of inefficient units in DEA and DEA-R is achieved using the CRA models based on the value efficiency (considering units that the manager defines as MPS). In the end, as applied research, a case study is carried out for clothing companies of a specific brand.
DEA-R, CRA, Value Efficiency
http://jamlu.liau.ac.ir/article-1-1181-en.html
http://jamlu.liau.ac.ir/article-1-1181-en.pdf