جستجوی مقالات مرتبط با کلیدواژه "‎efficiency" در نشریات گروه "ریاضی"

Deprivation and elimination of deprivation from different regions of the country to achieve sustainable development is one of the important issues in Iran. Therefore, the country's budget structure needs to be reformed. The purpose of this research is to evaluate the special view of the Islamic Consultative Assembly towards deprived areas in the amendment of the plan for eliminating deprivation, Note 14 of the budget law of the year 1401, using Data Envelopment Analysis (DEA) method. Since the decision-making units are the provinces of Iran, we have used the output-oriented CCR model to determine the efficiency of design modification, and then we have ranked it with the MAJ model. We have also determined important indicators in the allocation of credit to eliminate deprivation in provinces by using the AHP approach. Therefore, it is suggested that the note of this table should be deleted based on the text presented in a double-urgency plan agreed upon by main factions of the Parliament, and its credit should be distributed according to valid deprivation indicators. As well as this, we suggest that the requirements of each region should be met based on the latest statistics and relevant information.

Finding units with the most productive scale size (MPSS) is very important. The use of MPSS in ranking is thus the main idea in this paper. We propose an algorithm in DEA that ranks all extreme and non-extreme efficient DMUs in a number of steps. In this method, units with the most productive scale size are identified in each step and are then ranked. We finally show the application of the method using a numerical example.

With the growing trend in globalization and market competitiveness, process and resource optimization and the production of highly efficient products have become among the concerns of corporate managers. This research aims to evaluate and rank different polyethylene product grades produced at the Jam Petrochemical Complex using the Fuzzy Data Envelopment Analysis (FDEA) based upon fuzzy arithmetic [1]. The input-oriented fuzzy BCC model was suitable and applied to obtain the fuzzy efficiencies of different grades of polyethylene produced at the Jam Petrochemical Complex (13 DMUs) based on identified input and output indicators (Two inputs and three outputs). Then, a preference-degree approach is applied to compare and rank fuzzy DMU efficiencies. Based on the results, products HD52518, HD52505UV, and HM9450F were ranked first to third, respectively. The results highlight significant disparities in efficiency among the grades, providing a basis for targeted improvements.

This paper explores the resilience optimization of Iran's banking sector in the face of exchange rate shocks---critical macroeconomic disturbances with extensive consequences‎. ‎We develop a multi-sector macro-dynamic stochastic general equilibrium model encompassing essential economic components‎, ‎including firms‎, ‎government‎, ‎central bank‎, ‎and the banking sector‎. ‎This framework facilitates the simulation of the macroeconomic environment and allows for a thorough analysis of the banking sector's adaptive responses to exchange rate fluctuations‎. ‎Our findings reveal optimization strategies that effectively mitigate the adverse effects of these shocks while maintaining equilibrium in the broader economy‎. ‎Specifically‎, ‎we discover that while an initial positive exchange rate shock can enhance banking sector performance‎, ‎it ultimately triggers inflationary pressures that threaten profitability and operational stability in the medium to long term‎.

The efficiency score of the decision making units (DMUs) depends on the input and output values. The efficiency score of the DMU in the presence of undesirable outputs is greater or equal to the efficiency score of this DMU in the absence of undesirable outputs. To face this problem, we present a new ratio based data envelopment analysis (DEA-R) model to measure the effects of undesirable outputs on the efficiency of production units. In this regard, we first introduce the counterpart (hypothetical) units corresponding to the original DMUs. These units use the same amount of input to produce the same desirable outputs as the original DMUs, but produce a small amount of undesirable outputs compared to the original units. In the following, we use non-radial DEA-R models based on slacks corresponding to all the ratios of input components to desirable output and the ratios of undesirable output to desirable output to measure efficiency in the presence of undesirable outputs. Also, let's use the efficiency ratio of the main units to their corresponding counterpart units as a reduction factor to show the impact of undesirable outputs. To show the validity of the proposed approach, we evaluate the performance of thirty paper mills and present the results.

In traditional Data Envelopment Analysis (DEA) approaches, inputs and outputs are usually considered as exact and real values. The relative efficiency of the Decision Making Units (DMUs) is evaluated and it is known that the factors are inputs and/or outputs. However, there are some conditions under which the efficiency of DMUs should be calculated while the data are integer and ambiguous. Therefore, various integer DEA models have been proposed to determine the performance of DMUs when integer data and fuzzy factors are available. In addition, there are cases where the efficiency of DMUs should be determined when integer data and flexible factors are available. Therefore, some integer DEA methods have been proposed to calculate the performance of DMUs and specify the role of flexible measures when some of the data are integer and flexible factors are available. However, there are some situations where there are integer data, fuzzy integer measures and flexible factors. Therefore, this paper sheds light on the nature of the model to determine the efficiency of DMUs when there are integer inputs and/or outputs, flexible factors and fuzzy integer measures, and determines the role of factors with uncertain inputs or outputs. In fact, slacks are addressed and a slack-based efficiency measure (SBM) is defined to compute the performance of DMUs in the presence of flexible factors, integer data and fuzzy integer measures. The proposed approaches are demonstrated and illustrated using an example.

In order to improve the performance of inefficient decision-making units (DMU), it is important to find an efficient target. This target determines the amount of changes in inputs and outputs; by applying these changes, efficiency is achieved. The usual models in DEA always considered the problem of improving inefficient DMU and in this regard, they present a target as an efficient DMU. But in action, for some DMUs achieving that target in one step is difficult and even impossible. For this reason, finding intermediate target is very important. In this way, instead of an inefficient DMU becoming efficient in one step, this work is done in several steps and in this case the improvement is obtained gradually. In this paper, the efficiency of DMUs is evaluated using the CCR model, and then a sequence of intermediate targets is provided for each inefficient DMU. Moving in this direction will reduce the inefficiency of these DMUs.

This study aims to provide a comprehensive evaluation of the technical efficiency and scale of 15 suppliers of a production unit from 2020 to 2022. The research utilizes Data Envelopment Analysis (DEA) to analyze two scale assumptions that are generally employed: constant returns to scale (CRS), and variable returns to scale (VRS). The variables for the study were selected based on indicator availability, representation principles, and expert opinions. Investment, nonoperating expense cost and operating costs (including raw material costs, wages, and overhead costs) were considered as inputs, while net sales and return on investment were regarded as outputs. The results indicate that only two suppliers were operating at the optimal scale, and the scale efficiency of the supply chain displayed an increasing dispersion over the mentioned period. However, the net technical efficiency of the supply chain demonstrated an increasing concentration, suggesting an overall reduction in the gap between suppliers and an improvement in pure technical efficiency within the manufacturing unit's supply chain. This study provides valuable insights into the differences between suppliers from a macro perspective and offers guidance for manufacturing units looking to expand their supply chain.

In this paper, we evaluate the performance of decision-making units (DMUs) in semi-additive production technology in the presence of production trade-offs. We introduce the semi-additive production technology. The semi-additive technology is based on all the DMUs observed and the set of aggregated DMUs corresponding to these DMUs in data envelopment analysis (DEA). We obtain production trade-offs on input and output components in the production process in semi-additive technology. We present a single-stage model to measure efficiency in the presence of production trade-offs in semi-additive production technology. This model also identifies inefficiencies in all input and output components. We show an application of the presented model in the banking industry and at the end we bring the results of the paper.

A line location problem as a subdivision of facility location problem deals with finding a straight line in the plane, so that sum of weighted distances or maximum weighted distances from the line to the demand points is minimized. This paper provides a novel approach to study the semi-obnoxious median line location problem with Euclidean norm by using data envelopment analysis method. Since the presented procedure would consider lines as decision making units, so efficiency of lines is taken into account instead of their optimality. Moreover, due to the inherent uncertainty of the parameters of the line location problem in the real world such as weights or/and coordinates of demand points, the problem under interval data is studied in viewpoint of data envelopment analysis as well. Furthermore, some propositions and a numerical example are provided to investigate the problem. Finally, conclusion is given.

The two requirements of impartiality and equitability expressed with the principle of transfers are fulfilled by all objective functions in equitable multi-objective optimization. However, in some practical situations, the decision-maker believes these requirements should only be satisfied by a subset of objective functions. To solve the problem in this paper, we first divide the set of objective functions into two subsets, the subset given by the decision maker and its complement. Then, we apply the concepts of equitable efficiency and efficiency for these two subsets, respectively. Furthermore, we apply the mean and inequality measures for these subsets of objective functions and present the new mean-equity models for solving the location problem. We investigate the relationship between $2$-efficient solutions of the new mean-equity models and efficient solutions of the location problem.

In recent years, we have witnessed significant advancements in the production of solar cells with a reduction in cost and an increase in their efficiency. One of the stages in creating advancements in new cells is evaluating their performance under different conditions using simulations before their fabrication. In this article, the structure of a multi-junction solar cell composed of Ge layers, InAlGaAs alloys, and InAlGaP alloys will be comprehensively examined. To achieve the highest efficiency, the lowest absorbing layer of the solar cell (Ge solar cell) will initially be optically simulated and then electrically simulated. After optimizing the Ge solar cell, the intermediate layers between the cells (tunnel junctions) and then the upper absorbing layers will be optimized in sequence. Optimization of solar cells in each absorbing layer refers to selecting the appropriate thickness, impurity density, and molar percentage of the layers to achieve the highest efficiency. According to simulation results, an efficiency of over 49\% has been achieved for the 5-junction cell.

Today, achieving economic growth and development is one of the main and important goals of all countries, including Iran. Considering the special conditions of Iran and the existence of extensive sanctions, achieving economic growth is facing more and more severe restrictions; To overcome these limitations or at least adjust them, different solutions can be imagined, one of which is to follow the model of resistance economy. This research deals with the less-seen role of internal audit in realizing the components of a resistance economy. Based on this, the main goal of this research is to examine the role of internal audit quality in cost management with an emphasis on the components of resistance economy, which was prepared after studying the available sources, questionnaires based on previous studies, experts' opinions and internal audit executive instructions, which were approved Its validity and reliability were distributed among the community of working internal auditors and members of the internal audit association. The type and method of the present research is the type of applied research and its method is correlation. The research findings obtained by using confirmatory factor analysis and using structural equations (smart pls software) show that there is a significant relationship between the quality of internal audit in the realization of the components of resistance economy (cost management). There is a significant relationship between the quality of internal audit and economic efficiency. There is a significant relationship between internal audit quality and efficiency. There is a significant relationship between the quality of internal audit and effectiveness. Therefore, the results of the findings indicated this. that the quality of internal audit is effective in realizing the components of resistance economy (cost management).

‎Data envelopment analysis (DEA) is a methodology widely used for evaluating the relative performance of portfolios under a mean–variance framework‎. ‎However‎, ‎there has been little discussion of whether nonlinear models best suit this purpose‎. ‎Moreover‎, ‎when using DEA linear models‎, ‎the portfolio efficiency obtained is not comparable to those on the efficient portfolio frontier‎. ‎This is because a separable piecewise linear boundary usually below the efficient frontier is considered the efficient frontier‎, ‎so the model does not fully explore the possibility of portfolio benchmarks‎. ‎In this paper‎, ‎and with use of the dual-Lagrangian function‎, ‎we propose a linear model under a mean–variance framework to evaluate better the performance of portfolios relative to those on the efficient frontier‎.

This study aimed to investigate the supervision of the central bank with the audit and internal inspection units of banks and evaluate its impact on the efficiency of banking supervision. This research is applied in terms of purpose and in terms of descriptive-survey approach. In this study, all senior managers of bank branches in Tehran were considered as a statistical population of 150 people. According to Krejcie and Morgan's table, a society of this size required at least 108 statistical samples. In this study, a simple random sampling method was used to select statistical samples. The main tool used in this study was a researcher-made questionnaire that contained 22 items. In this questionnaire, the answers were designed based on a five-point Likert scale (from strongly disagree to strongly agree). The validity and reliability of this questionnaire were evaluated and confirmed in different ways. After distributing and collecting questionnaires and extracting data, descriptive and inferential analyses through SPSS and LISREL software were on the agenda. In this process, descriptive analyses were performed on the research variables, KMO test, Kolmograph-Smirnov test, confirmatory factor analysis and path analysis. Finally, the results showed that the interaction of the central bank supervision department with the internal audit units of banks has a strong and significant positive effect on the efficiency and effectiveness of banking supervision.

Data Envelopment Analysis (DEA) is one of the widely used methods in measuring the technical efficiency of organizations. Data envelopment analysis is a classical non-parametric technique based on mathematical programming, which is used to compare the evaluation of the efficiency of a set of similar decision-making units. Its significant advantage is that it does not need to determine parametric specifications (such as the production function) to get performance points. Data envelopment analysis is known as a valid and stable tool used in performance evaluation, which provides a single measure of performance for each unit relative to its peers. Even though the number of data envelopment analysis models is constantly increasing and each one has a specialized aspect, the basis of all is a number of main models, among which we can refer to the "Charnes, Cooper and Rhodes" models (1978) as CCR, in which the assumption of constant returns to scale (CRS) has been used in the analysis. There are different approaches to determining the effective factors on efficiency and productivity and how to measure the productivity of production factors. Among the investigated companies in the years 2019 to 2019, it was found that the technical efficiency of the companies decreased, the technological changes of the companies increased, the managerial efficiency of the companies decreased, the efficiency of the scale of the companies decreased, and the overall productivity of the companies faced a decrease.

The inverse Data Envelopment Analysis (InvDEA) is an exciting and notable issue in the DEA field. Various InvDEA models have been established to estimate the inherited input/output levels of the newly generated unit from merging units to achieve the pre-defined performance index. However, these models could not be employed when a deviation from the frontier is observed due to noise and random error in the data. In order to tackle this problem, the current paper contributes to InvDEA by introducing a novel method for estimating the inherited input/output levels of the merged unit to reach the pre-determined efficiency score in the level of significance $\alpha\in (0, 1)$. This paper also suggests a stochastic programming model for estimating the least possible efficiency score via the given merging. The managers can employ the results of this study to develop useful approaches to improve the efficiency of units. The validity of the proposed models is illustrated through a banking application.

Inverse data envelopment analysis (InvDEA) is a remarkable and popular management tool. This paper deals with one application of this tool. In fact, the problem of the combination of the units is investigated in the presence of negative data. The problem of combining units refers to the fact that a set of units create a new unit based on synergy to improve their performance. We use multiple objective programming for this purpose and suggest new models based on predetermined conditions for the new unit. The proposed models estimate inputs and outputs simultaneously. Importance advantages of the proposed models are i) We can follow multiple goals in the problem of combining units because multiple objective programming is applied. ii) Models can simultaneously estimate the inputs and outputs of the combined unit. iii) Unlike the existing methods in the InvDEA-based merging literature, the negative data do not need to be transferred to positive data. Finally, a numerical example is used to explain and validate the model proposed in this paper.

Data Envelopment Analysis (DEA) is a non-parametric mathematical programming method used to assess performance and measure the efficiency of Decision-making Units (DMUs) that operate with multiple concurrent inputs and outputs. The performance of these units is influenced by the utilization of input resources. While an increase in input utilization typically leads to higher production levels, there are scenarios where increased input usage results in decreased outputs. This phenomenon is termed congestion. Given that alleviating congestion can reduce costs and enhance production, it holds significant importance in economics. This paper introduces a method for identifying congestion based on a defined modeling framework. A DMU is considered congested when reducing inputs in at least one component leads to increased outputs in at least one component, and increasing inputs in at least one component can be achieved by reducing outputs in at least one component, without improvement in other indicators. The paper explores congestion in DMUs with both increasing and decreasing inputs.