In this paper, a data envelopment analysis (DEA) model with weight constraints is proposed to evaluate the work safety supervision in 18 districts. Conventional evaluation approaches of the work safety supervision only consider the simple data such as the number of accidents and the number of death in the accidents. There are two major shortcomings: the weights of criteria are difficult to dete...

in the classical data envelopment analysis (dea) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. in recent years, there are few researches on handling missing data. this paper suggests a new interval based approach to apply missing data, which is the modified version of kousmanen (2009) approach. first, the prop...

Data envelopment analysis (DEA) is an approach to measure the relative efficiency of decision-making units with multiple inputs and multiple outputs using mathematical programming. In the traditional DEA, it is assumed that we know the input or output role of each performance measure. But in some situations, the type of performance measure is unknown. These performance measures are called flexi...

This paper presents an integrated simulation, multivariate analysis and multiple decision analysis for railway system improvement and optimization. Furthermore, the integrated model is based on data envelopment analysis (DEA) and analytical hierarchy process (AHP) that is integrated with computer simulation [24]. The integrated DEA and AHP simulation model can be used for selecting optimum alte...

In transportation management the measure of systems efficiency is a key issue in order to verify the performances and propose the best countermeasure to achieve the prefixed goals. Many efforts have been made in this field to provide satisfactory answer to this problem. One of the most used methodologies is the Data Envelopment Analysis (DEA) that has been in many fields. The DEA technique is a...

This paper gives a new application of DEA to evaluate the scheduling solutions of parallel processing. It evaluates the scheduling solutions of parallel processing using the non-convex DEA model, FDH model. By introducing each solution of parallel processing scheduling as a DMU with some relevant inputs and outputs this paper shows that how the most efficient schedule(s) can be identified.

The fundamental weakness of a Data Envelopment Analysis (DEA) is its weak discrimination in cases when small number of Decision Making Units (DMU) have been compared. Therefore in such cases the basic DEA model is used in combination with other methods or additional constraints are added to the model. In this paper, the Cross-efficiency method has been combined with the Potential Method (PM).

This study analyses the technical efficiency of Saudi banks using a two-stage DEA-data envelopment analysis approach. In the first stage, we use a bootstrapped DEA–VRS model to identify the efficiency scores, and in the second stage, we use a bootstrapped truncated regression model to identify the covariates that explain technical efficiency. Policy implications are derived. 2010 Elsevier Ltd. ...

In humans, cytochrome P450 3A (CYP3A4) is a major enzyme involved in the metabolism of amiodarone (AM) to its major metabolite, desethylamiodarone (DEA). In rat, a commonly used animal model, metabolism of AM has not been well studied. To determine whether DEA is formed by CYP3A isoenzymes in the rat, microsomal protein was harvested from liver and intestine of male Sprague-Dawley rats. The met...

In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs,DEA-WEI models, in which convexity assumption is considered to be satisfied while the ratio data are constructed. Finally, an example of the modified DEA-WEI model is presented and c...