Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there ar...

The aim of this study is to provide a new two-stage DEA model with fuzzy multi-objective programming approach for evaluating the performance of companies listed in the Tehran Stock Exchange. In this study, a two-stage DEA model, different from the traditional model, we introduce for performance analysis. In this regard, the stable operation of companies, into two sub-process, have divided, whic...

This paper presents aggregated cost efficiency scores for a balanced panel of British and Irish credit institutions and relates these scores to loan loss reserves as a first step in investigating their usefulness as possible indicators of financial fragility. The efficiency scores are obtained using the two most popular methods of efficiency measurement – data envelopment analysis (DEA) and the...

Life-cycle (LC) approaches play a significant role in energy policy making to determine the environmental impacts associated with the choice of energy source. Data envelopment analysis (DEA) can be combined with LC approaches to provide quantitative benchmarks that orientate the performance of energy systems towards environmental sustainability, with different implications depending on the sele...

Traditional DEA does not take into account the environmental variables when analysis the electrical energy efficiency. In order to weigh the objective and subjective factors’ impact on industrial electrical energy efficiency, this paper attempts to analyze the China's 2011 industrial electrical energy efficiency step by step using DEA optimization model. The results showed that, electrical ener...

this paper presents a data envelopment analysis (dea) model combined with bootstrapping to assess performance of one of the data mining algorithms. we applied a two-step process for performance productivity analysis of insurance branches within a case study. first, using a dea model, the study analyzes the productivity of eighteen decision-making units (dmus). using a malmquist index, dea deter...

In data envelopment analysis (DEA), the curse of dimensionality problem may jeopardize accuracy or even relevance results when there is a relatively large dimension inputs and outputs, for samples. Recently, machine learning approach based on least absolute shrinkage selection operator (LASSO) variable was combined with sign-constrained convex nonparametric squares (SCNLS, special case DEA), du...

The spectroscopic and electrochemical properties of a series of four RuII polypyridyl complexes are reported. Compounds of the form [Ru(dmb)x(dea)3-x] (x ) 0-3), where dmb is 4,4′-dimethyl-2,2′-bipyridine and dea is 4,4′-bis(diethylamino)-2,2′-bipyridine, have been prepared and studied using static and time-resolved electronic and vibrational spectroscopies as a prelude to femtosecond spectrosc...

In this paper, the investment portfolio is formed based on the data mining algorithm of CHAID on the basis of the risk status criteria. In the next step, the second investment portfolio is created based on the decision rules extracted by the DEA-BCC model. The final portfolio is created through a two-objective mathematical programming model based on the Imperialist Competitive algorithm.