This paper introduces two virtual decision making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) into the data envelopment analysis (DEA). The resultant DEA models are, respectively, referred to as the data envelopment analysis with ideal and anti-ideal decision making units. One evaluates DMUs from the viewpoint of the best possible relative efficiency, while the other evaluate...

This paper proposes two-stage model for prioritizating decision making units (DMU) where each unit has multiple inputs and outputs. The rst stage model is a noncooperative game where each optimal input-output weight set of DMU is de ned by the Data Envelopment Analysis (DEA) and each DMU evaluates other DMUs by its own weights. The equilibrium state obtained from the rst stage motivates none of...

Determining the optimal scale size of a combined cycle power plant is inherently a complex problem often with multiple and conflicting criteria as well as uncertain factors. The complexity of the problem is compounded by the production of undesirable outputs and the presence of natural and managerial disposability. We propose a customized data envelopment analysis (DEA) method for solving the r...

This paper discusses and reviews the use of super-eciency approach in data envelopment analysis (DEA) sensitivity analyses. It is shown that super-eciency score can be decomposed into two data perturbation components of a particular test frontier decision making unit (DMU) and the remaining DMUs. As a result, DEA sensitivity analysis can be done in (1) a general situation where data for a tes...

An algorithm stral:egy is proposed for use with the assurance region (AR) approach in data envelopment analysis (DEA). The strategy addressed in this study characterizes and cla.5sifies all decision making units (DMUs) into several subsets, using the revised simplex method of linear programming. Then, each DMU subset is solved by a different algorithm. Experimental studies consisting of randoml...

DEA (Deta Envelopment Analysis) is a non-parametric technique for measuring the efficiency of DMUs (Decision Making Units)with common inputs and outputs [2,5]. viewpoint for each DMU because of taking a maximum ratio. During recent years, the issue of sensitivity and stability of data envelopment analysis results has been extensively studied. The first DEA sensitivity analysis paper by Charnes ...

Data envelopment analysis is a new field of interdisciplinary research in operations management science and mathematical economics. uses programming to evaluate the relationship between decision-making units with multiple inputs outputs (abbreviated as DMU). Effectiveness (DEA effective) judge whether DMU located on "frontier surface" production possibility set. This paper proposes method for e...

This paper proposes an efficient approach for optimizing the multiple quality characteristics (QCHs) in manufacturing applications on the Taguchi method using the super efficiency technique in data envelopment analysis (DEA). Each experiment in Taguchi’s orthogonal array (OA) is treated as a decision making unit (DMU) with multiple QCHs set as inputs or outputs. DMU’s efficiency is evaluated th...

In a variety of biological processes, eukaryotic cells use cilia to transport flow. Although cilia have a remarkably conserved internal molecular structure, experimental observations report very diverse kinematics. To address this diversity, we determine numerically the kinematics and energetics of the most efficient cilium. Specifically, we compute the time-periodic deformation of a wall-bound...

Data envelopment analysis (DEA) is a non-parametric technique for measuring and analyzing the relative efficiency of Decision-Making Unit (DMU) having multiple homogeneous types inputs outputs. Traditional DEA treats DMU as black boxes calculates their efficiencies by considering initial final But overall directly depended upon performances intermediate processes operations. In many situations,...