Sensitivity analysis of units with interval data in DEA

Sensitivity Analysis of Units with Interval Data in DEA

Data Envelopment Analysis (DEA) requires that the data for all inputs and outputs are known exactly. When some outputs and inputs are known decision variables, such as interval data and ordinal data, the DEA models becomes a nonlinear programming problem and is called imprecise DEA (IDEA). When data assume to be interval, decision making units (DMUs) can divide to three classes as follows: (I) ...

Sensitivity Analysis with Fuzzy Data in DEA

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 ...

Efficiency of decision making units in network DEA using interval data

New DEA/Location Models with Interval Data

Recently the concept of facility efficiency, which defined by data envelopment analysis (DEA), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. By combining the DEA models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

SENSITIVITY ANALYSIS OF EFFICIENT AND INEFFICIENT UNITS IN INTEGER-VALUED DATA ENVELOPMENT ANALYSIS

One of the issues in Data Envelopment Analysis (DEA) is sensitivity and stability region of the speci c decision making unit (DMU), included ecient and inecient DMUs. In sensitivity analysis of ecient DMUs,the largest region should be found namely stability region thatdata variations are only for ecient DMU under evaluation and the data for the remainingDMUs are assumed xed. Also ecient DMU u...