Hybrid robust, stochastic and possibilistic programming for closed-loop supply chain network design

被引:65
作者
Dehghan, Ehsan [1 ]
Nikabadi, Mohsen Shafiei [1 ]
Amiri, Maghsoud [2 ]
Jabbarzadeh, Armin [3 ]
机构
[1] Semnan Univ, Fac Econ & Management, Dept Ind Management, Semnan, Iran
[2] Allameh Tabatabai Univ, Fac Management & Accounting, Dept Ind Management, Tehran, Iran
[3] IUST, Dept Ind Engn, Tehran, Iran
关键词
Mixed-integer programming; Edible oil supply chain; Closed loop supply chain network design; Robust possibilistic programming; Stochastic programming; REVERSE LOGISTICS; BENDERS DECOMPOSITION; OPTIMIZATION MODEL; CONSTRAINTS; UNCERTAINTY; DEMAND; CONFIGURATION; GREEN; RISK;
D O I
10.1016/j.cie.2018.06.030
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The main goal of this study is to address gap in the area of Closed-loop Supply Chain Network Design (CLSCND) under the hybrid uncertain conditions. To do this, a multi-product and multi-period model is developed in an edible oil supply chain. Since the proposed model includes two kinds of uncertain parameters, the scenario- and fuzzy-based parameters, a novel Robust Stochastic-Possibilistic Programming (RSPP) are proposed to cope with uncertain parameters, based on the Me measure. Furthermore, the performance of the RSPP model is reviewed, its weaknesses and strengths are studied, and it is compared with the other models. Finally, the usefulness and applicability of the RSPP model are tested by the real industrial case study.
引用
收藏
页码:220 / 231
页数:12
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