In this study, we propose a new Artificial Neural Networks (ANN) training approach that closes the gap between ANN and Data Envelopment Analysis (DEA), and has the advantage of giving similar results to DEA and being easier to compute. Our method is based on extreme point selection in a bandwidth while determining the training set, and it gives better results than the traditional ANN approach. ...

This study proposes the Data Envelopment Analysis (DEA) ranking for resource allocation between Iran's Medical Universities based on a five years observation data (2004-2008). We compared the DEA ranking results with the traditional ranking approach applied by the Ministry of Health and Medical Education of Iran. Based on the DEA score the amount of budget is proposed for each university for th...

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...

Article history: Received 5 January 2014 Received in revised format 8 March 2014 Accepted 11 March 2014 Available online 12 March 2014 Measuring the relative efficiency of banking industry has been a popular subject among both practitioners and academicians. Data envelopment analysis (DEA) has been widely applied for different purposes. This paper presents an empirical investigation to measure ...

Supplier evaluation and selection are critical decision making processes that require consideration of a variety of attributes. Several studies have been performed for effective evaluation and selection of suppliers by utilizing several techniques such as linear weighting methods, mathematical programming models, statistical methods and AI based techniques. One of the successful evaluation meth...

In many data envelopment analysis (DEA) applications, the analyst always confronts the difficulty that the selected data set is not suitable to apply traditional DEA models for their poor discrimination. This paper presents an approach using Shannon’s entropy to improve the discrimination of traditional DEA models. In this approach, DEA efficiencies are first calculated for all possible variabl...

Current studies that use traditional data envelopment analysis (DEA) neglect the 100% market share restriction. This study adopts zero-sum gains data envelopment analysis to measure the efficiency scores of securities firms (SFs) and indicates that the traditional DEA model underestimates the efficiency scores of inefficient SFs. This research analyses 266 integrated securities firms in Taiwan ...

This paper considers a scheduling problem in flexible flow shops environment with the aim of minimizing two important criteria including makespan and cumulative tardiness of jobs. Since the proposed problem is known as an Np-hard problem in literature, we have to develop a meta-heuristic to solve it. We considered general structure of Genetic Algorithm (GA) and developed a new version of that b...

In this study we use data envelopment analysis (DEA), and an extension of DEA called value efficiency analysis (VEA), to explore the “production” of quality of life within counties in the mid-Atlantic region and the extent to which production frontiers and efficiency differ between rural and urban counties. These methods allow us to identify counties that are inefficient in their quality of lif...

This paper employs two stage data envelopment analysis (DEA) to investigate the efficiency effects of removing trade barriers on banking performance for a sample of Asian developing economies over the period 1997–2006. First, the DEA is employed to estimate the efficiency scores of banks. After that, the estimated DEA scores are analysed by density analysis and regressed on indices of trade bar...