نتایج جستجو برای: while conventional data envelopment analysis models set targets separately for each decision making unit
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the present study reports an analysis of response articles in four different disciplines in the social sciences, i.e., linguistics, english for specific purposes (esp), accounting, and psychology. the study has three phases: micro analysis, macro analysis, and e-mail interview. the results of the micro analysis indicate that a three-level linguistic pattern is used by the writers in order to cr...
This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we u...
this paper processes a combined method, based on vikor and data envelopment analysis (dea) to select the units with most efficiency. we utilize the vikor as compromise solution method. this research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. the problem involves belief parameters in the solution procedure. first, the alt...
In Data Envelopment Analysis, uncertain data are the inseparable part of real models. Natural models usually deal with uncertain and probable data. Many researchers prioritize these kinds of data. For instance, they study fuzzy data, interval data, probabilistic models etc. In this article, we proposed a method in which the decision making units are uncertain in their inputs and outputs. In the...
Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to...
Data Envelopment Analysis (DEA) is a method for determining the performance of units under evaluation of DMUs. Each decision-making unit using multiple inputs produces multiple outputs whose nature of outputs may be desirable or undesirable. Units whose performance score equals one are efficient. The concept of ranking decision makers because of the useful information they provide to decision m...
Abstract Conventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input output weights multiplier DEA these technologies interpreted as being most favorable for decision making unit (DMU) under assessment when latter is benchmarked against set all observed DMUs. In this paper we consider a very large clas...
Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative technical efficiency for each member of a set of peer decision making units (DMUs) with multiple inputs and multiple outputs. The original DEA models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which interval scale data can appe...
Abstract Data Envelopment Analysis (DEA) models give each decision making unit freedom to assign values the input-output weights maximising its efficiency score. However, there is no guarantee that optimal obtained from a DEA model are always positive which poses problem, in both theory and practice. This paper offers new linear programming deal with zero problem without restricting or placing ...
Context-Dependent Data Envelopment Analysis-Measuring Attractiveness and Progress with Interval Data
Data envelopment analysis (DEA) is a method for recognizing the efficient frontier of decision making units (DMUs).This paper presents a Context-dependent DEA which uses the interval inputs and outputs. Context-dependent approach with interval inputs and outputs can consider a set of DMUs against the special context. Each context shows an efficient frontier including DMUs in particular l...
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