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Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy

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  • Schröder, Tim
  • Lauven, Lars-Peter
  • Geldermann, Jutta

Abstract

Biorefineries can provide a product portfolio from renewable biomass similar to that of crude oil refineries. To operate biorefineries of any kind, however, the availability of biomass inputs is crucial and must be considered during planning. Here, we develop a planning approach that uses Geographic Information Systems (GIS) to account for spatially scattered biomass when optimizing a biorefinery’s location, capacity, and configuration. To deal with the challenges of a non-smooth objective function arising from the geographic data, higher dimensionality, and strict constraints, the planning problem is repeatedly decomposed by nesting an exact nonlinear program (NLP) inside an evolutionary strategy (ES) heuristic, which handles the spatial data from the GIS. We demonstrate the functionality of the algorithm and show how including spatial data improves the planning process by optimizing a synthesis gas biorefinery using this new planning approach.

Suggested Citation

  • Schröder, Tim & Lauven, Lars-Peter & Geldermann, Jutta, 2018. "Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1005-1019.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:3:p:1005-1019
    DOI: 10.1016/j.ejor.2017.01.016
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    2. Wolff, Michael & Becker, Tristan & Walther, Grit, 2023. "Long-term design and analysis of renewable fuel supply chains – An integrated approach considering seasonal resource availability," European Journal of Operational Research, Elsevier, vol. 304(2), pages 745-762.
    3. Mobtaker, A. & Ouhimmou, M. & Audy, J.-F. & Rönnqvist, M., 2021. "A review on decision support systems for tactical logistics planning in the context of forest bioeconomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    4. Olli-Jussi Korpinen & Mika Aalto & Raghu KC & Timo Tokola & Tapio Ranta, 2023. "Utilisation of Spatial Data in Energy Biomass Supply Chain Research—A Review," Energies, MDPI, vol. 16(2), pages 1-23, January.
    5. Senocak, Ahmet Alp & Guner Goren, Hacer, 2023. "Three-phase artificial intelligence-geographic information systems-based biomass network design approach: A case study in Denizli," Applied Energy, Elsevier, vol. 343(C).

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