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

Madjid Tavana, Rashed Khanjani Shiraz, Adel Hatami-Marbini

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1824-1839
Number of pages16
JournalJournal of the Operational Research Society
Volume65
Issue number12
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

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