دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Using semidefinite optimization for solving control systems of isothermal continuous stirred tank reactors optimal control problem
1
13
FA
R.
Dehghan
, Department of Mathematics, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman
rdehghan110@gmail.com
Y
M.
kiyanpour
Department of Mathematics, Guilan University, Rasht
N
In this paper, an optimization method is used for solving a fractional optimal control problem with significant applications in chemical engineering. The considered optimal control is the control system of the isothermal continuous stirred tank reactors. The Riemann-Liouville fractional derivative is used to describe the mathematical model of control system. For solving the fractional optimal control problem, at first by using different order of moments, we achieve an optimal control problem in space of moments, and then by using the discretization technique of variables, we will get a positive semidefinite optimization problem. Finally, by solving the equivalent optimization problem, we obtain the solution of the considered fractional optimal control problem.
Moments, Semidefinite optimization, Fractional derivative, Optimal control
http://jamlu.liau.ac.ir/article-1-1351-en.html
http://jamlu.liau.ac.ir/article-1-1351-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
A Mixed Integer Programming Formulation and an Effective Algorithm for Time Depended Petrol Station Replenishment Problem with Time Windows
15
37
FA
A.
Dolatnejad
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran
a_dolatnejad@aut.ac.ir
N
S. M.
Mirhassani
Department of Mathematics and Computer Science, Amirkabir University of Technology Tehran
a_mirhassani@aut.ac.ir
N
M.
Yousefikhoshbakht
Department of Mathematics, Faculty of sciences, Bu-Ali Sina University, Hamedan
yousefikhoshbakht@gmail.com
Y
In order to improve service quality and satisfy specific delivery requests from different customers, suppliers are tending to afford more efficient and convenient distribution services rather traditional approaches. For example, customers may change preferred hours of receiving their orders, and due to this, wholesalers must distribute goods in different time windows. In this article, for the first time, the Time Depended Petrol Station Replenishment Problem with Time Windows (TDPSRPTW) is considered, and a new mathematical programming and a column generation method is proposed to solve it. This version of the PSRPTW is motivated by the fact that in some circumstances traffic conditions play an important role and cannot be ignored in order to perform a realistic optimization. The TDPSRPTW consists in optimally routing a limited heterogeneous fleet of vehicles of fixed capacity during a working day. It should be noticed that expense and time of the travel on the curve are dependent on the time that is spent on the curve, and delivery to a customer must be done based on time windows. The aim here is to minimize the number of used vehicles and the total time spent, provided that travel times of goods be known at the beginning of the optimization. The algorithm has been tested in a set of instances including 15 stations in the literature, and it has been proven that the suggested algorithm is very efficient.
Petrol Station Replenishment Problem with Time Windows, Time Depended Routes, Mathematical programming, Column Generation
http://jamlu.liau.ac.ir/article-1-1102-en.html
http://jamlu.liau.ac.ir/article-1-1102-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Research and Development Project Portfolio Selection Based on Compound real Options Approach and Robust Combinatorial optimization
39
62
FA
M.
Montajabiha
Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin
Montajabiha.Mahsa@qiau.ac.ir
Y
A.R.
Arshadi Khamseh
Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran,
Ar_arshadi@khu.ac.ir
N
B.
Afshar-Nadjafi
Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin
Afsharnb@alum.sharif.edu
N
The worldwide rivalry of commerce leads organizations to focus on selecting the best project portfolio among available projects through utilizing their scarce resources in the most effective manner. To accomplish this, organizations should consider the intrinsic uncertainty in projects on the basis of an appropriate evaluation technique with regard to the flexibility in investment decision-making along an optimization framework. In the current research here, the problem of project selection under uncertain environment is formulated by using robust optimization model for dealing with the complexities and uncertainties regarding the construction of a project portfolio. First of all, a general mathematical formulation which can address compound real option evaluation is employed to correct the deficiency of traditional approaches to evaluate the worth of multi-step problems. Then, a project selection model is developed by robust optimization, which is effective for solving problems under uncertainty. Finally, by supposing the budget of the organization to be rare, the model maximizes the combinatorial robust optimization worth of projects and is solved according to the combinatorial robust optimization algorithm. A comprehensive example is provided to illustrate the proposed decision approach.
Project Portfolio Selection, Combinatorial Robust Optimization, Uncertainty, N_Fold Compound Options
http://jamlu.liau.ac.ir/article-1-883-en.html
http://jamlu.liau.ac.ir/article-1-883-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
An Analytical and comparative approach for using Metaheuristic algorithms for job shop scheduling problems
63
76
FA
P.
Samouei
Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan
P.samouei@basu.ac.ir
N
P.
Fattahi
, Department of Industrial Engineering, Alzahra University, Tehran
Fattahi@alzahra.ac.ir
Y
One of the most important problems in research and applied fields of production management is a suitable scheduling for different operations. So, there are many approaches for job workshop or job non-workshop scheduling problems. Since job workshop scheduling problems (JSP) belong to NP-Hard class, some metaheuristics methods such as Tabu Search, Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization have used in different papers to solve such problems. This paper tries to solve these problems by using these algorithms and compares their conclusions. Therefore, problems with different sizes are used and are analyzed by time, quantified, and parametric approaches.
Job shop scheduling problem, Tabu Search (TS), Simulated Annealing (SA), Genetic Algorithm(GA), Particle Swarm Optimization(PSO)
http://jamlu.liau.ac.ir/article-1-854-en.html
http://jamlu.liau.ac.ir/article-1-854-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Locating emergency facilities with variable radius of coverage under uncertainty (Case Study: Khorasan Province)
77
93
FA
P.
Ghasemi
Department of Industrial Engineering, Islamic Azad University, Tehran South Branch, Tehran
peiman.ghasemi@aut.ac.ir
N
A.
Shojaie
Islamic Azad University- South Tehran Branch
amir@ashojaie.com
Y
Relief logistics is one of the most effective tools in the crisis management. Growing number of global disasters and crisis events in Iran in the last decade indicates the importance of relief logistics planning more than before. Facility location of the resources allocation is the basic instrument in relief logistics before, in, and after each crisis. In this paper, covering radius of facilities is considered as a discrete variable with a step function toward cost. The proposed maximal covering location model determines the place, type, and capacity of the relief facility that will be required. Uncertainty is involved in the problem as a limited scenario; meanwhile, the above model has been formulated with two aims: maximizing the coverage and minimizing the budget. Then the problem has been solved by the GAMS software, and the results have been investigated on real and random data. Moreover, the results of stable optimized model and random optimized model have been compared.
Facility Location, Maximal covering, Variable covering radius, distribution network, relief logistic
http://jamlu.liau.ac.ir/article-1-988-en.html
http://jamlu.liau.ac.ir/article-1-988-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Presenting Network data envelopment analysis models by a combination of desired and undesired intermediate and final outputs
95
116
FA
M.
Shafiei Nikabadi
Department of Industrial Management, Semnan University
shafiei@semnan.ac.ir
Y
K.
Yakideh
Department of Industrial Management, Guilan University
yakideh@Guilan.ac.ir
N
A.
oveysi omran
Department of Industrial Management, Semnan University
akramoveysi@gmail.com
N
This study was conducted to investigate the overall efficiency of production and transmission of electricity. For this purpose, sixteen areas of production and transmission of electricity industry of Iran were selected as decision-making units. Based on Khalili and Shahmir’s model, a mathematical model was proposed that includes two stages of the production and transmission of electricity. In this proposed model, at the end stage of the production, output variables were considered which do not enter to next stage of production. In the second phase, in addition to inputs received from the production stage, other input variables were considered that are not included in the model from the previous stage. In the first stage, variables of domestic consumption of power stations and consumed fuel were regarded as input variables, and maximum production load variables, special production, gross production, efficiency, nominal power of power station, and practical power of power station were considered as outpout variables. In the second stage, variables of maximum production load, especial production, gross production, capacity of power transmission posts and transmission lines were considered as input variables, while delivered energy variable was considered as desired output, and energy losses were considered as undesired output variable. Results of the two stages indicated that districts of Azerbaijan, Isfahan, Tehran, Khorasan, Khuzestan, Semnan, Kerman, and Fars were efficient.
electricity generation, electricity transmission, envelopment analysis of network data, undesired outcomes, intermediate desired output
http://jamlu.liau.ac.ir/article-1-1169-en.html
http://jamlu.liau.ac.ir/article-1-1169-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Linear Modeling to Determine the Set of Common Weights InNetwork Structure
117
135
FA
J.
pourmahmoud
Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz
pourmahmoud@azaruniv.ac.ir
Y
Z.
zeynali
Department of Applied Mathematics, Azarbaijan Shahid Madani University, Tabriz
zeynali49@azaruniv.edu
N
In traditional DEA models, one faces the challenge of zero and unequal weights for evaluating each decision-making unit (DMU). On the other hand, for measuring the efficiency in these models, the system is considered as a black box, disregarding its internal processes. One of the strategies applied to deal with this problem is to use common weights of each input/output in all DMUs. In practice, most decision-making units evaluated together include internal processes with different structures, referred to as network structure. Similar to the traditional DEA models, a challenge exists for the network structures. In a number of cases, common weight sets in two-stage network structure have been proposed that do not include network general structures. This paper aims at proposing the same challenge for network general structures to solve the problem of network general structures through a newly proposed model of common weights set. The models are applied on kao’s examples to illustrate the results.
Common weight, Network data envelopment analysis, Multi-objective programming, goal programming
http://jamlu.liau.ac.ir/article-1-1303-en.html
http://jamlu.liau.ac.ir/article-1-1303-en.pdf
دانشگاه آزاد اسلامی واحد لاهیجان
Journal of Operational Research In Its Applications ( Applied Mathematics ) - Lahijan Azad University
2251-7286
2251-9807
14
1
2017
4
1
Integrated reverse logistics network design considering the quality of returned products using genetic algorithms
137
156
FA
N.
tarin
Rahbord Shomal Institute of Higher Education, Rasht
tarin_nasser@yahoo.com
Y
A.
Azar
, Department of Management & Economics, Tarbiat Modarres University, Tehran
AZARA@modares.ac.ir
N
S.A.
ebrahimi
University of Guilan, Rasht
EBRAHIMI908@YAHOO.COM
N
In many industries, manufacturers─for various reasons─have to collect products that have been used by customers. Then, depending on the status of the returned products, appropriate decisions are made to process the products. In this paper, issues such as inventory control and product planning optimization in the environment of integrated reverse logistics have been focused on. The assumed logistics network here consisted of two stages. In the first stage, returns were subject to quality inspection using the qualitative thresholds definitions, for which they were separated and sent to the appropriate lines for recovery or disposal. In the second stage, having different amounts sent to each line, a mixed integer optimization algorithm (MILP) has been proposed to lower the total cost of the network. The proposed model, considering the minimization of the costs, is of NP-Hard problem types in which the problem increases exponentially. Therefore, in this study, Genetic Algorithm has been used to solve the model.
reverse logistics, product quality returns, inventory control, mixed integer optimization algorithm, genetic algorithm
http://jamlu.liau.ac.ir/article-1-1316-en.html
http://jamlu.liau.ac.ir/article-1-1316-en.pdf