The existing Data Envelopment Analysis models for evaluating the relative eciency of a set of decision making units by using various inputs to produce various outputs are limited to crisp data in crisp production possibility set. In this paper, rst of all the production possibility set is extended to the fuzzy production possibility set by extension principle in constant return to scale, and th...

this research proposes a methodology for ranking decision making units byusing a goal programming model.we suggest a two phases procedure. in phase1, by using some dea problems for each pair of units, we construct a pairwisecomparison matrix. then this matrix is utilized to rank the units via the goalprogramming model.

data envelopment analysis (dea) is a wide range of mathematical models that used for measuring the relative efficiency of a set of harmonic units whit similar inputs and outputs. this model calculates some different weight for input and output variables in each decision making model. this variation in similar weights caused some critiques to this method. from 1991 some linear and nonlinear mode...

data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) with multiple inputs and outputs. the traditional dea treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. this carries the notion of missing some intermediate measures in the process of changing the inputs to...

in conventional dea models, decision making units (dmus) are generally assumed as a black-box while the performance of decision making sub-units (dmsus) and their importance play crucial roles in  analyzing the performance of systems which have internal processes. the present paper introduces an ideal network which have efficient processes and next purposes a new approach for evaluating importa...

This research proposes a methodology for ranking decision making units byusing a goal programming model.We suggest a two phases procedure. In phase1, by using some DEA problems for each pair of units, we construct a pairwisecomparison matrix. Then this matrix is utilized to rank the units via the goalprogramming model.

Super eciency data envelopment analysis(DEA) model can be used in ranking the performanceof ecient decision making units(DMUs). In DEA, non-extreme ecient unitshave a super eciency score one and the existing super eciency DEA models do notprovide a complete ranking about these units. In this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient units.