Data envelopment analysis is computationally intensive. The standard approach requires the solution of as many LPs as there are points in the data domain, each with as many columns. This number is frequently in the thousands and multi-period DEA amplifies the problem. Enhancements that reduce the size of the LPs are possible and a new scheme consisting of partitioning the domain offers more tim...

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

Quantifying cartilage contact stress is paramount to understanding hip osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses. Previous applications of DEA have underestimated cartilage stresses and yielded unrealistic contact patterns because they assumed constant cartilage thickness and/or concentric joint geometry. The stu...

Problem solved: an air-stable 2-pyridyl borane that can effectively couple to a wide range of aryl and heteroaryl halides and pseudohalides has evaded the synthesis community for decades. The discovery that Cu(DEA)(2) powerfully enables palladium-mediated cross-couplings with air-stable boronates 1 has finally provided a general solution to this problem. DEA=diethanolamine, DMF=N,N'-dimethylfor...

-Organizations need to work on productivity improvement in order to enhance their operational performances. A number of works have taken efforts in efficiency evaluation and ranking using analytic methods such as the data envelopment analysis (DEA). However, few works have highlighted the relationship among significant factors that affect productivity. Performing efficiency evaluation and ranki...

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...

Abstract: The radial measures of classical DEA models (CCR, BCC) are incomplete, they are only separate measures of input and output efficiency and their efficiency index omit the non-zero input and output slacks. Enhanced Russell graph measure (ERM) eliminates these deficiencies. All of the existing fuzzy DEA models are extension of CCR or BCC model, efficiencies of DMUs, ultimately, are solut...

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic a...

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/ or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, ...