Multi-Stage Adaptive Robust Optimization over Bioconversion Product and Process Networks with Uncertain Feedstock Price and Biofuel Demand

Daniel J. Garcia, Jian Gong, Fengqi You

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Uncertainties abound in the biofuel industry and other product and process networks. Some key uncertainties include feedstock price uncertainty and product demand uncertainty. Product demand can guide strategic decisions such as sizing of capital equipment, and feedstock price can affect operational purchasing and processing decisions. We propose a multi-stage adaptive robust optimization approach to handle both of these different types of uncertainties in order to find the minimum total annualized cost of a bioconversion product and process network. Robustness of the solutions are controlled by budgets of the uncertainty, allowing for various solutions with varying levels of conservativeness. The minimum total annualized cost among the robust solutions ranges from $17.9M/y to $22.5M/y. A solution with a good compromise between risk and cost was identified with a cost of $21.9M/y.

Original languageEnglish (US)
Title of host publication26 European Symposium on Computer Aided Process Engineering, 2016
EditorsZdravko Kravanja, Milos Bogataj
PublisherElsevier B.V.
Pages217-222
Number of pages6
ISBN (Print)9780444634283
DOIs
StatePublished - Jan 1 2016

Publication series

NameComputer Aided Chemical Engineering
Volume38
ISSN (Print)1570-7946

Keywords

  • adaptive robust optimization
  • biofuels
  • uncertainty

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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