Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers ...

occupational accidents severely deteriorate human capital, and hence negatively affect the productivity andcompetitiveness. but despite these negative points, there are still deficiencies in safety managementperformance and indicators. therefore the safety issue needs an active management. for this reason, thewriter has proposed an approach to evaluate organizations based on safety management. ...

inthis article we offer a method of ranking contractors by using dea based onanalysis deficit and ahp. the process of hierarchical analysis (ahp) byproviding scales from paired comparison matrix, performs the contractor’sprioritizing choice. but ahp has some problems and to solve those problems,jahanshahloo and his colleagues presented a new model which uses dea andstandard deviation. in this a...

the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

the objective of this study is to determine factors affecting the technical efficiency of the inshore fisheries in kuala terengganu. data for the study was collected from a survey conducted between june and august 2007 where 100 fishermen in 14 villages were chosen by stratified sampling. data envelopment analysis (dea) and tobit analysis were employed to determine the technical efficiency leve...

this paper aims at providing a new model based on data envelopment analysis (dea) to prioritize project risks. it is clear that the large amounts of involved capitals, the long term of infrastructure projects’ implementation, and the project management problems in on-time completion of projects indicate the necessity of paying particular attention to this issue and conducting applied research i...

the basic models of data envelopment analysis (dea) are designed in such a way that the values of input and output indicators should be identified and known in them. in other words, these models are not used to consider inaccurate, interval, fuzzy, judgment data. in this paper, the aim is to not only review the past researches about the efficiency of the units by interval data and represent the...

The main goal of this paper is to propose a new approach for efficiency measurement and ranking of stocks. Data envelopment analysis (DEA) is one of the popular and applicable techniques that can be used to reach this goal. However, there are always concerns about negative data and uncertainty in financial markets. Since the classical DEA models cannot deal with negative and imprecise values, i...

In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit (DMU) in the best light in comparison to all the other DMUs, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use...

All countries have responded with a wide range of measures to stop the propagation coronavirus. We apply best tube interval data envelopment analysis, in order evaluate efficiency quarantine using imprecise data. Using Oxford COVID-19 Government Response Tracker’s (OxCGRT) and given method, we construct time series assessment government responses COVID-19. In addition, separate all examined int...