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

Author

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  • Quddus, Md Abdul
  • Chowdhury, Sudipta
  • Marufuzzaman, Mohammad
  • Yu, Fei
  • Bian, Linkan

Abstract

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.

Suggested Citation

  • Quddus, Md Abdul & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Yu, Fei & Bian, Linkan, 2018. "A two-stage chance-constrained stochastic programming model for a bio-fuel supply chain network," International Journal of Production Economics, Elsevier, vol. 195(C), pages 27-44.
    • Handle: RePEc:eee:proeco:v:195:y:2018:i:c:p:27-44
    DOI: 10.1016/j.ijpe.2017.09.019
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