A two-stage chance-constrained stochastic programming model for a bio-fuel supply chain network

被引:83
|
作者
Quddus, Md Abdul [1 ]
Chowdhury, Sudipta [1 ]
Marufuzzaman, Mohammad [1 ]
Yu, Fei [2 ]
Bian, Linkan [1 ]
机构
[1] Mississippi State Univ, Dept Ind & Syst Engn, Starkville, MS 39759 USA
[2] Mississippi State Univ, Dept Agr & Biol Engn, Starkvile, MS 39759 USA
关键词
Bio-fuel supply chain network; Multi-modal facility; Chance-constrained optimization; Sample average approximation; SAMPLE AVERAGE APPROXIMATION; MUNICIPAL SOLID-WASTE; EXPECTED VALUE; PROCESSING DEPOTS; DISRUPTION RISKS; LOCATION DESIGN; OPTIMIZATION; MANAGEMENT; DECOMPOSITION; UNCERTAINTY;
D O I
10.1016/j.ijpe.2017.09.019
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study presents a two-stage chance-constrained stochastic programming model that captures the uncertainties due to feedstock seasonality in a bio-fuel supply chain network. The chance-constraint ensures that, with a high probability, Municipal Solid Waste (MSW) will be utilized for bio-fuel production. To solve our proposed optimization model, we use a combined sample average approximation algorithm. We use the state of Mississippi as a testing ground to visualize and validate the modeling results. Our computational experiments reveal some insightful results about the impact of MSW utilization on a bio-fuel supply chain network performance.
引用
收藏
页码:27 / 44
页数:18
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