A new chance-constrained DEA model with birandom input and output data

Date

2013-11-27

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Springer

Type

Article

Peer reviewed

Yes

Abstract

The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-constrained DEA model with birandom input and output data. A super-efficiency model with birandom constraints is formulated and a non-linear deterministic equivalent model is obtained to solve the super-efficiency model. The non-linear model is converted into a model with quadratic constraints to solve the non-linear deterministic model. Furthermore, a sensitivity analysis is performed to assess the robustness of the proposed super-efficiency model. Finally, two numerical examples are presented to demonstrate the applicability of the proposed chance-constrained DEA model and sensitivity analysis.

Description

Keywords

Data Envelopment Analysis, Chance-constrained programming, Birandom variables, Quadratic constraints, Super-efficiency

Citation

Tavana, M., Shiraz, R. K. and Hatami-Marbini, A. (2014) A new chance-constrained DEA model with birandom input and output data. Journal of the Operational Research Society, 65 (12), pp. 1824-1839

Rights

Research Institute