STOCHASTIC COST EFFICIENCY EVALUATION OF A SUPPLY CHAIN

Abstract

The main goal of the paper is a consideration of cost efficiency evaluationmodels related to some supply chain when dealing with imprecise data. Data envelopmentanalysis (DEA) method is a non-parametric mathematical programming approach toassess the performance. This method is proposed for deterministic data and it canbe generalized to inaccurate data, while considering real world applications. Here weconsider data as random variables and after reviewing and introducing new models toevaluate cost efficiencies related to the special circumstances of the supply chain usingDEA, these models are developed to probabilistic form. Also, deterministic and linearequivalents are proposed using the symmetric error structure of normal distributions. Atfinal, by a numerical example, the proposed models are examined to show relationshipsof results.