This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...

Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and sever...

As data envelopment analysis (DEA) has been developed both in theory and application, the calculation of models become more and more important. Although many DEA software tools have been built for the calculation of the DEA models, there are some deficiencies in embedding them into enterprise management information system (MIS). As an extension of this work, an idea was generated in this paper,...

Proposed in this study is a hybrid model for supporting the performance of a department within Amir Kabir University in Iran. The proposal is a two-stage model designed to fully rank the organizational departments where each faculty has multiple inputs and outputs. First, the Data Envelopment Analysis (DEA) separately formulates each pair of units. In the second stage, the pair-wise evaluation ...

In this paper, a novel approach has been proposed to rank police administration units on the basis of their effective enforcement of crime prevention measures using Data Envelopment Analysis (DEA) and Clustering. The proposed approach will offer an effective mechanism not only to rank police administration units but also provide an evaluation tool to monitor the implementation of crime preventi...

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper introduces a neural network backpropagation Data Envelopment Analysis. Neural network requirements of computer memo...

The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...

This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysi...

We report a combined experimental and theoretical investigation of dissociative electron attachment (DEA) to the nucleobase uracil. Using ion momentum imaging experiments employing a DEA reaction microscope we have measured 3-dimensional momentum distributions of specific anionic fragments following DEA to uracil by 6 eV electrons. From the measured anion fragment kinetic energy we determine th...

There has been an ever growing concern to measure efficiency of decision making units (DMUs). Parametric approaches have been the popular methods for measuring the same. Data Envelope Analysis (DEA) is an addition in this domain. This paper is an attempt to understand the concept of DEA approach. DEA is a Linear Programming Problem that provides a means of calculating apparent efficiency levels...