Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors

被引：79

作者：

Izadikhah, Mohammad ^{[1
]}

Saen, Reza Farzipoor ^{[2
]}

机构：

[1] Islamic Azad Univ, Dept Math, Coll Sci, Arak Branch, POB 38135-567, Arak, Iran

[2] Islamic Azad Univ, Dept Ind Management, Fac Management & Accounting, Karaj Branch, POB 31485-313, Karaj, Iran

来源：

COMPUTERS & OPERATIONS RESEARCH | 2018年 / 100卷

关键词：

Sustainability of supply chain; Chance-constrained data envelopment analysis (DEA); Intermediate products; Efficiency; Two-stage DEA model; Undesirable data; Stochastic data; DATA ENVELOPMENT ANALYSIS; ENVIRONMENTAL PERFORMANCE; EFFICIENCY DECOMPOSITION; INTERMEDIATE PRODUCTS; WEIGHT RESTRICTIONS; GENETIC ALGORITHM; NEURAL-NETWORK; ORDINAL DATA; SELECTION; INPUT;

D O I：

10.1016/j.cor.2017.10.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Sustainable supply chain is recognized as a key component of corporate responsibility. Despite conventional data envelopment analysis (DEA) models that view decision making units (DMUs) as black boxes, two-stage DEA models take into account intermediate measures within a DMU. However, there might be stochastic data. Objective of this paper is to present a new stochastic two-stage DEA model in the presence of undesirable data. We present some linear models that obtain lower and upper bounds of efficiencies of stages 1 and 2. Also, we propose a linear model that calculates overall efficiency of DMUs. Meanwhile, we extend our proposed model for dealing with stochastic data in the presence of undesirable data. A case study demonstrates applicability of our approach. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：343 / 367

页数：25

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