A robust super-efficiency data envelopment analysis model for ranking of provincial gas companies in Iran

被引：57

作者：

Sadjadi, S. J. ^{[1
]}

Omrani, H. ^{[1
,2
]}

Abdollahzadeh, S. ^{[2
]}

Alinaghian, M. ^{[1
]}

Mohammadi, H. ^{[3
]}

机构：

[1] Iran Univ Sci & Technol, Dept Ind Engn, Tehran, Iran

[2] Urmia Univ Technol, Dept Ind Engn, Orumiyeh, Iran

[3] Qom Gas Co, Qom, Iran

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 09期

关键词：

Data envelopment analysis; Robust optimization; Uncertainty; Rank; DEA; OPTIMIZATION; PRODUCTIVITY; BENCHMARKING; PERFORMANCE; INDUSTRY; PRICE;

D O I：

10.1016/j.eswa.2011.02.120

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Conventional super-efficiency data envelopment analysis (DEA) models require the exact information of inputs or outputs. However, in many real world applications this simple assumption does not hold. Stochastic super-efficiency is one of recent methods which could handle uncertainty in data. Stochastic super-efficiency DEA models are normally formulated based on chance constraint programming. The method is used to estimate the efficiency of various decision making units (DMUs). In stochastic chance constraint super-efficiency DEA, the distinction of probability distribution function for input/output data is difficult and also, in several cases, there is not enough data for estimating of distribution function. We present a new method which incorporates the robust counterpart of super-efficiency DEA. The perturbation and uncertainty in data is assumed as ellipsoidal set and the robust super-efficiency DEA model is extended. The implementation of the proposed method of this paper is applied for ranking different gas companies in Iran. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：10875 / 10881

页数：7

共 44 条

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