An optimization model for green supply chain management by using a big data analytic approach

被引:195
|
作者
Zhao, Rui [1 ,2 ]
Liu, Yiyun [1 ]
Zhang, Ning [3 ]
Huang, Tao [1 ]
机构
[1] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China
[2] Southwest Jiaotong Univ, State Prov Joint Engn Res Lab Geospatial Informat, Chengdu 611756, Peoples R China
[3] Jinan Univ, Inst Resource Environm & Sustainable Dev, Dept Econ, Coll Econ, Guangzhou 510632, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Hazardous materials; Inherent risk; Carbon emissions; Multi-objective optimization; Green supply chain management; Big data analysis; CLEANER PRODUCTION; OPERATIONAL PRACTICES; PREDICTIVE ANALYTICS; RISK-ASSESSMENT; DATA SCIENCE; GAME-THEORY; PERFORMANCE; DESIGN; SYSTEM; IMPLEMENTATION;
D O I
10.1016/j.jclepro.2016.03.006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents a multi-objective optimization model for a green supply chain management scheme that minimizes the inherent risk occurred by hazardous materials, associated carbon emission and economic cost. The model related parameters are capitalized on a big data analysis. Three scenarios are proposed to improve green supply chain management. The first scenario divides optimization into three options: the first involves minimizing risk and then dealing with carbon emissions (and thus economic cost); the second minimizes both risk and carbon emissions first, with the ultimate goal of minimizing overall cost; and the third option attempts to minimize risk, carbon emissions, and economic cost simultaneously. This paper provides a case study to verify the optimization model. Finally, the limitations of this research and approach are discussed to lay a foundation for further improvement. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1085 / 1097
页数:13
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