Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Demand Management using Autoregressive-Time Series Modeling in Mobile Value-Added Services
9
30
FA
Mohammad Hossein
Vaghefzadeh
Ph.D student, Amir Kabir University of Technology.
m.vaghefzadeh@aut.ac.ir
Behrooz
Karimi
Professor, Amir Kabir University of Technology.
b.karimi@aut.ac.ir
Emerging of Value-Added Services (VAS) as a modern supply sector in the field of mobile networks requires some elements such as content providers, intermediate companies, as well as operators, which called service supply chain. Formation of such service supply chain produces some challenges consist of management and modeling of demand trend, customer behavior and Bullwhip Effect. This paper aims to perform a precise evaluation on trend of demand in the mobile VAS area and also the Bullwhip Effect. Considering Conditional Autoregressive effects on demand trend, it has been recommended to use of ARCH class models in time series analysis. The results of this paper show that ARMA (1,1)/EGARCH (1,1) model is more powerful than GJR and GARCH models in reducing the Bullwhip Effect of this special time series demand.
Value-Added Services,Service Supply Chain Management,Demand Forecasting,Bullwhip Effect,ARCH Class Models
https://jimp.sbu.ac.ir/article_87171.html
https://jimp.sbu.ac.ir/article_87171_4af05fc110fd83f5a6d080e713e3968a.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Designing the Mechanism for Choosing the Appropriate Maintenance Strategy
31
69
FA
Abolfazl
Sherafat
Assistant Professor, Imam Javad Higher Education Institute, Yazd.
sherafat.a@ut.ac.ir
Ali
Mohaghar
0000-0002-9844-1714
Associate Professor, University of Tehran.
amohaghar@ut.ac.ir
Farahnaz
Karimi
B.A., Yazd University.
karimi346@gmail.com
Seyyed Mohammad Reza
Davoodi
Assistant Professor, Dehaghan Branch, Islamic Azad University, Dehaghan.
smrdavoodi@yahoo.com
Today, organizations are under tremendous pressure to continuously enhance their capabilities to create value for customers and improve the effectiveness of equipment. Without the proper equipment organization will face major challenges in competition and customer satisfaction. Inappropriate performance of equipment is a phenomenon that any manufacturing organization faces with it. The strategy is selected against this phenomenon, depends on several factors. This issue becomes more important when the production line is continuous. In electricity company providers because of supplying strategic product issue is more complex. In this study, tried to determine the factors affecting the conditions in relation inappropriate performance of equipment to define this phenomenon. Therefor, using a three-stage approach of Grounded theory, with inductive method to study the phenomenon of improper performance of equipment has been studied and with gathering the experts opinion this industry and analyzing relevant data in five categories and 24 subcategories and 90 characteristic this phenomenon has been described and then how to choose appropriate strategies for different conditions explained.
Strategy,Inappropriate Performance of Equipment,Grounded theory
https://jimp.sbu.ac.ir/article_87172.html
https://jimp.sbu.ac.ir/article_87172_2ec151f7c2bd0314f716b7c25b3549f6.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Presenting a Maximum Capture Model by Calculating the Interval Facility Number and Taking into Account the Cost Objective Function
71
83
FA
Amir
Alimi
Ph.D student, Ferdowsi University of Mashhad.
amiralimi2005@yahoo.com
Mostafa
Kazemi
Professor, Ferdowsi University of Mashhad.
kazemi@um.ac.ir
Ali Reza
Pooya
0000-0001-6000-3535
Associate professor, Ferdowsi University of Mashhad.
alirezapooya@gmail.com
Zahra
Naji Azimi
Associate professor, Ferdowsi University of Mashhad.
znajiazimi@um.ac.ir
The maximum capture problem seeks to find a suitable location for facilities in the network space and in a competitive condition. In this problem, the new company intends to enter the market with the aim of capturing more demand. In this study, the cost factor is considered to be a separate objective function and a bi-objective model is proposed. The number of facilities parameter is considered to be an interval and for its upper and lower bounds calculations two models are proposed. To obtain upper bound a model with the maximum capture objective and the maximum budget constraint and to obtain lower bound a model with the minimum cost objective and the minimum market share constraint. To solve the proposed model, a goal programming method is used. The steps of the research methodology and modelling are shown in a case study from Yazd city. The results show that if the weight of the objective functions is assumed to be equal and the investor neglect 7 % of the market share, 55% of initial investment could be saved.
Competitive Facility Location,Maximum Capture,Interval Parameter,Multi-Objective Programming,Goal Programming,Opening Cost
https://jimp.sbu.ac.ir/article_87173.html
https://jimp.sbu.ac.ir/article_87173_9f3002ddc5dbf456c929c753568a5aa2.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Multi-Objective Problem of Services Assignment to Bank Clustered Customers
85
110
FA
Seyyed Mohammad Ali
Khatami Firouzabadi
Associate Professor, Allameh Tabataba’i University.
smakhf@hotmail.com
Seyyed Mohammad Taghi
Taghavi Fard
0000-0002-4212-2079
Associate Professor, Allameh Tabataba’i University.
dr.taghavifard@gmail.com
Seyyed Khalil
Sajjadi
Ph.D student, Allameh Tabataba’i University.
khalil_sajjadi2006@yahoo.com
Jahanyar
Bamdad Soufi
Assistant Professor, Allameh Tabataba’i University.
bamdadsoofi@yahoo.com
Knowing customer behavior patterns clustering and assigning them is one of the most important purposes for banks. In this research five criteria of each customer including Recency Frequency Monetary Loan and Deferred were extracted from the bank database during one year and then clustered using the customer's K-Means algorithm. A multi-objective model of bank service allocation was then designed for each of the clusters. The purpose of the designed model was to increase customer satisfaction reduce costs and reduce risk of allocating services. Given the fact that the problem does a unique optimal solution and each client feature has a probability distribution function a simulation approach was used to solve it. In order to determine the neighbor optimal solution of the Simulated Annealing algorithm neighboring solutions were used and a simulation model was implemented. The results showed a significant improvement over the current situation. In this research we used Weka and R-Studio software for data mining and Arena for simulation for optimization.
Clustering,Multi-Objective Assignment Model,Optimization,Simulation
https://jimp.sbu.ac.ir/article_87174.html
https://jimp.sbu.ac.ir/article_87174_4b6b1bec051d72985d4befd1cf65a3b1.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Combination of the Analytic Network Process Method and Multi-Objective Decision-Making in order to Predict and Reduce the Future Risks of Suppliers
111
134
FA
Mehrnoush
Monfared
M.A., Department of Industrial Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
mehrnoush.monfared@gmail.com
Mohammad Hosein
Arman
Assistant Professor, Department of Industrial Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
hosein.arman@yahoo.com
Masoud
Barati
Assistant Professor, Department of Industrial Management, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
barati_masoud@yahoo.com
The essential risks of suppliers increase complexity and vulnerability of supply chain and sometimes cause the disruptions. These risks should be predicted and to coping with them some solutions must be provided beforehand. It is aimed at identifying the disruptive risks in the supply chain of Foolad steel and then decreasing their potential effects for the next four periods. According to experts of the company, the graphite electrode is strategically the most important material as its risks disrupt the supply chain. The weighs of these risks were determined by using ANP and accordingly the most important risk was the risk of non-flexibility of suppliers with a weight of 0.5436. Other risks, the risk of long delivery orders, the risk of low quality and the risk of price increases, have the weights of 0.1911,0.1716 and 0.0937, respectively. Then, a multi-objective function model was developed that each objective function aims to minimize one risk. This model was solved by two methods, absolute priority method and goal programming, and finally the results were compared to each other.
Multi Suppliers Model,Resilient Supply Chain,Analytic Network Process,Absolute Priority Method,Goal Programming
https://jimp.sbu.ac.ir/article_87175.html
https://jimp.sbu.ac.ir/article_87175_8c1990d1f816a2c53a56cd0a59fa915f.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Evaluating Service Quality of Airlines using a Hybrid Fuzzy MADM Approach
135
164
FA
Mohammad Reza
Taghizadeh Yazdi
Associate Professor, University of Tehran.
mrtaghizadeh@ut.ac.ir
Sima
Sabzali Rezaei
M.A. Student, University of Tehran.
sima.rezaee@ut.ac.ir
Mir Seyyed Mohammad Mohsen
Emamat
Ph.D Student, Allameh Tabataba’i University.
emamat@atu.ac.ir
Hengameh
Alikhani
M.A. Student, University of Tehran.
hengameh.alikhani@ut.ac.ir
The quality of the services is one of the main factors in the competitiveness of the companies, and managers are keen to measure it accurately so that they can compare themselves with competitors. The purpose of this research is to rank the Iranian airlines in terms of the quality of services provided to travelers on domestic flights. Research previously conducted into service quality is examined in the first part of this study, and the service quality measurement attributes are determined and weighted by using the FAHP method. Then, using the FVIKOR method and based on the opinions of experts, the airlines are evaluated. The results of this study showed that the FAHP extent analysis method may lead to incorrect results. Hence, in this study, the Wang and Chen method is used to calculate the weight of attributes in FAHP. The results showed that responsiveness, compensation procedures, staff attitude and flight safety are more important in measuring service quality. The study showed that the top companies in terms of service quality include Ata, Zagros and Caspian.
Multi-Attribute Decision-Making (MADM),Fuzzy Analytical Hierarchy Process,Fuzzy VIKOR,Quality of Service,Airlines
https://jimp.sbu.ac.ir/article_87176.html
https://jimp.sbu.ac.ir/article_87176_bb11b6a745fc816cb676eb51f7257580.pdf
Shahid Beheshti University
Journal of Industrial Management Perspective
2251-9874
2645-4165
8
2
2018
08
23
Solving a Bi-Objective Multi-Mode Project Scheduling Problem with Regard to Payment Planning and Constrained Resources using NSGA-II Algorithm
165
187
FA
Ebrahim
Gholizadeh
MSc. Student, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.
ebgh1368@gmail.com
Behrouz
Afshar Najafi
0000-0002-3391-8411
Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.
afsharnb@alum.sharif.edu
This research studies the multi-mode project scheduling problem aiming to planning of payments considering limited resources. This model tries to propose a schedule as much as possible close to reality with taking the realistic assumptions into account. In the proposed model, renewable resources (including manpower, machinery, and equipment) as well as non-renewable resources (including consumption and money) are simultaneously considered. Then, the issues of scheduling and planning the project payment with the objectives of increasing the NPV of the project and reducing the completion time of the project in are examined. In doing so, a nonlinear mathematical programming model is presented based on the assumptions made in the problem space, to formulate the problem. Then, to validate the model, several random instances are designed in different dimensions and solved by GAMS software and ε-constraint method. To tackle the problem in large dimensions, we also proposed the NSGA-II algorithm. Finally, efficiency of the developed methodology is measured by comparing the results with ε-constraint method.
Multi-Mode Project Scheduling,NPV,Project Payment Scheduling,ε-Constraint Method,NSGA-II Algorithm
https://jimp.sbu.ac.ir/article_87177.html
https://jimp.sbu.ac.ir/article_87177_6d038de5a95e2524fc35cf66a239a6e6.pdf