Determine the most productive scale of a production unit using a two-stage process based on the demand level
Abbasali
Noora
Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran
author
Faranak
Hosseinzadeh Saljooghi
Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran
author
Maryam
Khodadadi
Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran
author
text
article
2018
per
In the real world, there are decision-making units in which the production process can be considered as a two-stage or multi-stage process. In order to evaluate these types of units, the network data envelopment analysis method is used. In this paper, Two-stage units have been investigated, which in the two-stage process are the outputs of the first stage of the second stage inputs, which are referred to as "middle sizes".The purpose of this research is to determine the most effective scale of the production unit scale using a two-step process based on the demand level.In this regard, while determining the units of MPSS with ordinary DEA methods, we will generalize it in two-stage models.Then, the maximum and minimum amount of production, the production units that are in the most efficient scale of the scale, are obtained at each of the stages separately and then generalized for the whole process.We consider supply and demand as two output indicators and we determine the demand level for each step separately and then the whole process so that we can obtain the maximum and minimum amount of demand.
Journal of Decisions and Operations Research
Ayandegan Institute of Higher Education, Tonekabon, Iran
2538-5097
2
v.
2
no.
2018
107
115
https://www.journal-dmor.ir/article_57317_71ba9707ff45a74b1f148cbeb635d94f.pdf
dx.doi.org/10.22105/dmor.2018.57317
Evaluation of the performance and ranking of the efficiency of Tehran branches of a private bank using two-stage data envelope analysis and Borda ranking technique
Ehsan
Vaezi
Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
author
Mehdi
Memarpour
Department of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
author
text
article
2018
per
Banks are among the economic centers of the country, whose performance regarding promotion of productivity and efficiency, leads to economic development of the country. Accordingly, investigation of the status of the performance and efficiency of a bank will be influenced by the performance and efficiency of that bank’s branches. The aim of this study is to investigate the efficiency and ranking of 121 branches of a certain private bank in Tehran. For this purpose, first two-stage data envelope analysis has been used to obtain the efficiency of banks accurately using 7 indices as the input variable, 4 indices as the intermediate variable, and 1 index as the output variable. The results of the research indicated that in the first stage of the two-stage data envelope analysis, 51 branches were found to be efficient, which was reduced to 18 branches in the second stage. As the accurate efficiency of each branch was determined following two stages, for ranking the branches that had an efficiency of one, Sexton, Anderson-Peterson and Charnes-Cooper efficiency method was employed. In the last stage, using Borda technique, the results obtained from the previous models were combined and the final ranking of the bank’s branches was determined.
Journal of Decisions and Operations Research
Ayandegan Institute of Higher Education, Tonekabon, Iran
2538-5097
2
v.
2
no.
2018
116
129
https://www.journal-dmor.ir/article_55774_2320f9e7c3ba099e4a1c97fae7d67a30.pdf
dx.doi.org/10.22105/dmor.2018.55774
A new model of fuzzy two-stage data envelopment analysis with variable-return to scale
Mohammad Javad
Goleij
Department of Industrial Engineering, Ayandegan Institute of Higher Education, Iran
author
text
article
2018
per
One of the best tools to evaluate the performance is DEA technique. Data envelopment analysis technique is a tool for ranking and identifying efficient and inefficient units. Since, in many cases, the decision-making units in organization have an intermediate (middle values) and also in some cases the real world, available values for inputs and outputs are obscure (ambiguous) and uncertain, and using classic data envelopment model does not reach us to a certain result. Also, return on the scale is a very important argument in data envelopment analysis and economics and can provide us with useful information about the status of the decision-maker units.In this paper, we present a new model for fuzzy two-stage data envelopment analysis and to evaluate this efficiency, we study the efficiency of industrial workshops between 10 and 49 employees. The efficiency of industrial workshops is evaluated by province. The results are the importance of the proposed model.
Journal of Decisions and Operations Research
Ayandegan Institute of Higher Education, Tonekabon, Iran
2538-5097
2
v.
2
no.
2018
130
146
https://www.journal-dmor.ir/article_54145_8d1be1d45e27566d85fdb0cbf77aa159.pdf
dx.doi.org/10.22105/dmor.2018.54145
Presenting a bi-objective vendor managed inventory model with fuzzy demand for multiple vendor
Vida
Karbasi bonab
Department of Industrial Engineering, Islamic Azad University, bonab Branch, Bonab, Iran
author
Mahdi
Yousefi Nejad Attari
Department of Industrial Engineering, Islamic Azad University, bonab Branch, Bonab, Iran
author
Ensiyeh
Neishabouri
Department of Industrial Engineering, Islamic Azad University, bonab Branch, Bonab, Iran
author
text
article
2018
per
Vendor managed inventory (VMI) is one of the popular strategies to manage inventory control system, in this strategy, the vendor is responsible for controlling and replenishment the inventory of retailers. In this paper, a bi-objective vendor managed inventory (BOVMI) model with fuzzy demand was investigated for a supply chain problem with multiple vendors and retailers, the fuzzy demand is formulated using trapezoidal fuzzy number (TrFN) where the centroid defuzzification method is employed to defuzzify fuzzy output functions. The vendor confronts two constraints: number of orders and available budget and minimizing the total inventory cost and optimizing the warehouse space are the two objectives of the model. Since the proposed model is formulated ino a bi-objective integer nonlinear programming (INLP) problem, an non-dominated Sorting genetic algorithm-II (NSGA-II) has been developed to find Pareto front solution. To improve the performance of algorithm has been calibrated using Taguchi method. Finally, conclusions are made and future research works are recommended.
Journal of Decisions and Operations Research
Ayandegan Institute of Higher Education, Tonekabon, Iran
2538-5097
2
v.
2
no.
2018
147
168
https://www.journal-dmor.ir/article_57316_3eb40e82bc6cfc79a1b86b2ad87cc049.pdf
dx.doi.org/10.22105/dmor.2018.57316
Multi-Purpose Transmission expansion planning in Smart Grids Considering the resources responsible for load and security of the system
Mohammad
Saberi
Department of Electrical Engineering, Ayandegan Institute of Higher Education, Iran
author
Mehdi
Hatef
Sama Siyahkal vocational training center, Islamic Azad University, Lahijan branch, Siahkal, Iran
author
text
article
2018
per
The purpose of Transmission expansion planning (TEP) is to find the required network lines with the lowest investment cost So that the future burden will be provided economically by observing the system security indicators. Due to the uncertainty of the load, Distributed wind power and Responsive resources to load and competitive markets for Transmission expansion planning, Faced with challenges that require new models to be felt more than ever. In this paper, a multi-objective TEP model is presented taking into account investment costs, Responsive resources to load, along with an index for determining system security. These target functions are optimized for obtaining a non-dominant solution set based on operator priorities (cost or risk), using pareto power evolutionary algorithms based on multi-objective particle pool optimization (SPEA2-MOPSO). The proposed model is numerically verified on the modified IEEE RTS 24- bus and 118-bus systems. According to the simulation results, the proposed model can provide information regarding variants of risks and coordinate the optimum planning and DR solutions.
Journal of Decisions and Operations Research
Ayandegan Institute of Higher Education, Tonekabon, Iran
2538-5097
2
v.
2
no.
2018
169
178
https://www.journal-dmor.ir/article_57753_bcbe9bc5dca77a6f1b43479d7961f03a.pdf
dx.doi.org/10.22105/dmor.2018.57753