STOCHASTIC COST EFFICIENCY EVALUATION OF A SUPPLY CHAIN

M. MIRBOLOUKI

The main goal of the paper is a consideration of cost eciency evaluation

models related to some supply chain when dealing with imprecise data. Data envelopment

analysis (DEA) method is a non-parametric mathematical programming approach to

assess the performance. This method is proposed for deterministic data and it can

be generalized to inaccurate data, while considering real world applications. Here we

consider data as random variables and after reviewing and introducing new models to

evaluate cost eciencies related to the special circumstances of the supply chain using

DEA, these models are developed to probabilistic form. Also, deterministic and linear

equivalents are proposed using the symmetric error structure of normal distributions. At

nal, by a numerical example, the proposed models are examined to show relationships

of results.

Data envelopment analysis, Supply chain management, Performance measures, Symmetric error structure, Cost eciency.