in the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. in these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. this paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. in the prese...

one of the major problems in data envelopment analysis (dea) is to determine the projection of inefficient decision making units (dmus) into the efficient frontier. in conventional dea models, inputs and outputs of inefficient dmus alter arbitrarily for reaching to the efficient frontier. nevertheless, sometimes the ability of dmus is defined and restricted. moreover, there are situations in th...

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among...

The Cuckoo optimization algorithm (COA) is developed for solving single-objective problems and it cannot be used for solving multi-objective problems. So the multi-objective cuckoo optimization algorithm based on data envelopment analysis (DEA) is developed in this paper and it can gain the efficient Pareto frontiers. This algorithm is presented by the CCR model of DEA and the output-oriented a...

since data envelopment analysis (dea) introduced in 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems. recently dea has been extended to examine the efficiency of decision making units (dmus) with two-stage network structures or processes, where the outputs from the first stage are intermediate measures that make up the inputs of t...

the present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. cross-efficiency evaluation is an effective way of ranking decisionmaking units (dmus) in data envelopment analysis (dea). conventional dea models assume nonnegativevalues for inputs and outputs. however, we know that unlike return and skewness, varianceis the on...

Data envelopment analysis (DEA) is one of the widely used methods to measure efficiency scores decision making units (DMUs). Conventional DEA unable consider both uncertainty in data and makers’ (DMs) judgments evaluations. This study, address shortcomings conventional DEA, proposes a new best worst method (BWM)- robust credibility (BWM-RCDEA) model estimate DMUs considering DMs’ preferences un...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...

In many organizations and financial institutions, we don't always have acsses to inputs and outputs to evaluate the decision-making units (DMUs), but rather only a ratio of inputs to outputs ( or reverse) might be available. In DEA, cost efficiency determines input standards based on input costs. In multi-stage network DEA processes, in addition to input standards, cost efficiency would determi...

Optimization of diagnostic efficiency by mathematic modeling rather than logic is getting momentum in the medical spectrum using computer data analysis. Effective evaluation of disease diagnosis is considered to be one of the research problems getting relief and reduction of cost. Thus the diagnosis of Acute Myocardial Infarction (AMI) by DEA-ANN method is a significant development received by ...