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

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

International Journal of Production Economics, 2018, vol. 195, issue C, 27-44

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.

Keywords: Bio-fuel supply chain network; Multi-modal facility; Chance-constrained optimization; Sample average approximation (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527317303031
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:195:y:2018:i:c:p:27-44

DOI: 10.1016/j.ijpe.2017.09.019

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().