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Showing 6 results for pourmahmoud
Dr Jafar Pourmahmoud, Dr Naser Bafek Sharak,
Volume 11, Issue 1 (9-2020)
Abstract
Cost efficiency models evaluate the ability of decision-making units (DMUs) to produce current
outputs at minimal cost. In real applications, the observed values of the input-output data and
their corresponding input prices are imprecise and vague. This paper employs a fuzzy data
envelopment analysis (Fuzzy DEA) method to study cost efficiency of DMUs. In previous studies
on the cost efficiency, no attention has been paid to the issue of ranking problem in fuzzy
environment. In addition, adequate accuracy is ignored in regards to appropriate range of fuzzy
cost efficiency scores. In this study, the proposed method is applied to assess fuzzy cost efficiency
in accordance with the -level based approach. In this method, data information is considered
as triangular fuzzy numbers. The main idea is to convert the fuzzy DEA model into a family of
parametric crisp models to estimate the lower and upper bounds of the a-cut of the membership
functions of the cost efficiency measures. Moreover, the problem of ranking DMUs is investigated
based on the fuzzy cost efficiency, using a new method. Finally, the proposed method is illustrated
applying a numerical example, and then comparisons between the proposed method and previous
approaches are carried out.
Dr. Jafar Pourmahmoud, Mrs Maedeh Gholam Azad,
Volume 11, Issue 1 (9-2020)
Abstract
Predictive analytics is an area of statistics that deals with extracting information from data and using
that to predict trends and behavioral patterns. Many mathematical models have been developed and
used for prediction, and in some cases, they have been found to be very strong and reliable. This
paper studies different mathematical and statistical approaches for events prediction. The main goal
of this research is to design and construct a hybrid prediction method for events prediction, based on
Logistic Regression (LR) method and Data Envelopment Analysis (DEA) technique. In this study, a
novel hybrid algorithm was developed, and considering the kind of collected data, LR method was
applied for input selection, and the capability of the additive (ADD) model of DEA was examined to
predict the occurrence or non-occurrence of the events. To apply the proposed approach, the selected
disease for the case study was a stroke. The results showed that any patient who was placed on the
frontier has had a stroke by one or more risk factors. On the other hand, the observations that were
not on the frontier had not suffered from a stroke. The overall accuracy of 88.5 percentages was
obtained for the developed method
Prof. Jafar Pourmahmoud, Dr Naser Kaheh,
Volume 13, Issue 1 (6-2022)
Abstract
In the traditional cost-efficiency model, the information about each decision unit includes inputs, outputs, and the input prices are fixed and specific. In practice, the price of the inputs often fluctuates at different times, and these prices for the decision-making unit are time-dependent. By the traditional method, the efficiency of decision units is impossible in the presence of time-dependent input prices. On the other hand, the exact method of cost-efficiency calculation is also difficult and time-consuming. In this study, a new method for calculating cost efficiency of decision making units with time-dependent prices during a period of time using numerical integral is presented. As the information of the decision-making units varies over time, a method for calculating their cost efficiency accurately is presented. however, the exact method is difficult or impossible to be solved in some cases. Therefore, in this study, an approximate method for calculating the cost efficiency in the given state is presented. This is a suitable replacement for the precise method. The efficiency of decision making units at different time is measured and the units are ranked using the proposed method. Finally, a numerical example is provided to indicate the method and compare it with the precise method. This study shows that the efficiency obtained by the approximate method is very close to the efficiency obtained by the exact method, and at the same time, the calculation speed increases.
Dr Jafar Pourmahmoud , Dr Davood Norouzi Bene ,
Volume 13, Issue 2 (12-2022)
Abstract
Data Envelopment Analysis is one of the most appropriate methods in Evaluation of decision-making units in the real world. That is why researchers have always tried to improve and develop existing methods and approaches in this field. Network Data Envelopment Analysis is used to evaluate the efficiency of network systems by considering processes within divisions. In the evaluation of network systems, one of the challenges is the presence of undesirable and non-discretionary data in the system. Not many conducted have been done about the simultaneous presence of these factors in general two-stage network systems. For this reason, by extending CCR model and combining some methods in this study, we presented a model that is able to evaluate two-stage systems with the mentioned conditions. One of the strengths of the proposed model in this study is the achievement of the efficiency of the system and divisions simultaneously. At the end of the article, we analyzed the results with a numerical example. The results show the ability of the presented model in evaluating the systems under investigation.
Jafar Pourmahmoud,
Volume 14, Issue 1 (6-2023)
Abstract
In cost efficiency models, the capability of producing observed outputs of a target decision making unit (DMU) is evaluated by its minimum cost. Traditional cost efficiency models are considered for situations where data set is known for each DMU, while, some of them are imprecise in practice. Several studies have carried out to evaluate cost efficiency using fuzzy data envelopment analysis (DEA) methods for dealing with the imprecise data that have drawbacks. The issue of presenting improve strategy is ignored for inefficient units, as well as the applied models are not easily implemented. This paper proposes a new extension to evaluate fuzzy cost efficiency using fuzzy extended multiplication and division operations. This method offers a fully fuzzy model with triangular fuzzy input-output data along with triangular fuzzy input prices. In the proposed extension, a new definition of fuzzy cost efficiency is suggested based on the extended operations. Finally, a numerical example is provided to show the applicability of the proposed models.
Jafar Pourmahmoud, Mahdi Eini, Davood Darvishi Salokolaei, Saeid Mehrabian,
Volume 14, Issue 2 (12-2023)
Abstract
In the evaluation of decision making units with classical models of data envelopment analysis, it is assumed that the factors are deterministic. In some decision-making problems, the amount of inputs or outputs of the units is not exactly known and it is a three-parameter interval in grey form. In this case, it is recommended to choose the factors from their center of gravity. In the classic models of data envelopment analysis, all factors are also considered desirable, but in real problems there are undesirable factors too which cannot be used to evaluate problems with undesirable inputs and undesirable outputs. In this paper, a model is presented for calculating the efficiency of decision making units in the presence of the center of gravity of undesirable three-parameter interval grey undesirable factors based on the combination of strong and weak disposability principles. To this end, the proposed method is discussed with a practical example.
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