Classic data envelopment analysis (DEA) models determine the efficiency of productive units, called decision making units (DMUs). DEA uses as its methodology the equiproportional reduction of inputs or increase of outputs and the finding of a single target for each DMU. This target does not incorporate the preference of the decision maker. Later works propose obtaining alternative targets based...

In data envelopment analysis (DEA) efficient decision making units (DMUs) are of primary importance as they define the efficient frontier. By means of modified CCR model, in which the test DMU is excluded from the reference set, we are able to determine what perturbations of data can be tolerated before frontier DMUs become nonfrontier. In this paper we discuss simultaneous data perturbations i...

This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/incre...

DEA model selection is problematic. The estimated efficiency for any DMU depends on the inputs and outputs included in the model. It also depends on the number of outputs plus inputs. It is clearly important to select parsimonious specifications and to avoid as far as possible models that assign full high efficiency ratings to DMUs that operate in unusual ways (mavericks). A new method for mode...

Data Envelopment Analysis (DEA) is the use of non-parametric mathematical programming that useful for measuring efficiency Decision Making Unit (DMU) an organization. This study uses Cooper and Rhodes (CCR) method known as DEA-CCR multiplier which aims to determine weight value each input output variable DMU being evaluated, but it not sufficient measure optimization. To get efficient a referen...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-p...

Reverse Engineering (RE) of mechanical parts consists in creating a 3D virtual model using data that are often gathered by 3D measurement systems like laser scanners. The resulting point cloud is then transformed into a geometrical model. The purpose of RE activity is to make maintenance or redesign operations easier. The boundary of the literature is the component, isolated from its product as...

The Delight Design Platform Project is managed by The University of Tokyo as part of the Crossministerial Strategic Innovation Program (SIP) which is organized by Cabinet Office, Government of Japan. This project recommends using 1DCAE design tools in the concept phase of the product development. In the Delight Design Platform, new product concepts are simulated and evaluated as 1DCAE models. O...

Cross-efficiency evaluation is an effective approach to ranking decision making units (DMUs) that utilize multiple inputs to produce multiple outputs. Its models can usually be developed in a way that is either aggressive or benevolent to other DMUs, depending upon the decision maker (DM)’s subjective preference to the two extreme cases. This paper proposes several new data envelopment analysis...

In this paper, we will propose a Slacks-Based measure (SBM) of efficiency in DEA. This scalar measure deals directly with the input surplus and the output shortage of the decision making unit (DMU) concerned. It is unit invariant and monotone decreasing with respect to input surplus and output shortage. Furthermore, this measure is decided only by consulting with the reference set of the DMU an...