Symmetric Error Structure in Stochastic DEA

Stochastic programming is an approach for modeling and solving optimization problemthat include uncertain data. chance constrained programming is one of the most importantmethods of stochastic programming. in many real world data envelopment analysis(dea) models, exact amount of data can not be determined. therefore several researchersproposed methods to evaluate stochastic efficiency of units with random inputs and/or outputs.most of these methods are nonlinear. in this paper by introducing symmetric errorstructure for random variables, a linear from of stochastic ccr is provided. finally, theproposed model is applied on an example.