IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v200y2022icp694-705.html
   My bibliography  Save this article

Risk-based multistage stochastic mixed-integer optimization for biofuel supply chain management under multiple uncertainties

Author

Listed:
  • Zarei, Mohammadamin
  • Shams, Mohammad H.
  • Niaz, Haider
  • Won, Wangyun
  • Lee, Chul-Jin
  • Liu, J. Jay

Abstract

CO2 emissions from the transportation sector account for 22% of global emissions. Blending biofuels with fossil fuels is a promising method for reducing these emissions and ensuring energy security. One of the most important and challenging aspects of the biofuel production process is the design of supply chains that integrate various types of biomasses under multiple uncertainties. The aim of this study is to address this issue by proposing a multi-stage stochastic program for strategic and tactical planning in multi-feedstock biofuel supply chain networks under uncertainties of biomass supply and biofuel demand. The proposed model minimizes the total annualized cost by selecting raw materials, positioning production facilities, placing storage facilities, and defining deferral paths for each feedstock. In addition, a new dynamic method of the conditional value at risk is adopted to consider the risk hedge. Deterministic, stochastic, and risk-based models are compared, and case studies based on the South Korean context show the effectiveness of the model and the algorithm. Computational results indicate that considering risk can increase biofuel expected production cost by up to 88%. It also shows that biomass transportation is the most affected part of the supply chain in risk assessment. Furthermore, it indicates that a value of 0.5 is the most effective risk aversion factor.

Suggested Citation

  • Zarei, Mohammadamin & Shams, Mohammad H. & Niaz, Haider & Won, Wangyun & Lee, Chul-Jin & Liu, J. Jay, 2022. "Risk-based multistage stochastic mixed-integer optimization for biofuel supply chain management under multiple uncertainties," Renewable Energy, Elsevier, vol. 200(C), pages 694-705.
    • Handle: RePEc:eee:renene:v:200:y:2022:i:c:p:694-705
    DOI: 10.1016/j.renene.2022.10.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122014963
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.10.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Homem-de-Mello, Tito & Pagnoncelli, Bernardo K., 2016. "Risk aversion in multistage stochastic programming: A modeling and algorithmic perspective," European Journal of Operational Research, Elsevier, vol. 249(1), pages 188-199.
    2. Fangzhou Sun & Maichel M. Aguayo & Rahul Ramachandran & Subhash C. Sarin, 2018. "Biomass feedstock supply chain design – a taxonomic review and a decomposition-based methodology," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5626-5659, September.
    3. Govindan, Kannan & Fattahi, Mohammad, 2017. "Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 680-699.
    4. Bairamzadeh, Samira & Saidi-Mehrabad, Mohammad & Pishvaee, Mir Saman, 2018. "Modelling different types of uncertainty in biofuel supply network design and planning: A robust optimization approach," Renewable Energy, Elsevier, vol. 116(PA), pages 500-517.
    5. Dickson, Rofice & Ryu, Jun-Hyung & Liu, J. Jay, 2018. "Optimal plant design for integrated biorefinery producing bioethanol and protein from Saccharina japonica: A superstructure-based approach," Energy, Elsevier, vol. 164(C), pages 1257-1270.
    6. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    7. Fattahi, Mohammad & Govindan, Kannan, 2018. "A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 534-567.
    8. Jadidbonab, Mohammad & Babaei, Ebrahim & Mohammadi-ivatloo, Behnam, 2019. "CVaR-constrained scheduling strategy for smart multi carrier energy hub considering demand response and compressed air energy storage," Energy, Elsevier, vol. 174(C), pages 1238-1250.
    9. Xie, Fei & Huang, Yongxi, 2018. "A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 130-148.
    10. Kang, Seongwhan & Heo, Seongmin & Realff, Matthew J. & Lee, Jay H., 2020. "Three-stage design of high-resolution microalgae-based biofuel supply chain using geographic information system," Applied Energy, Elsevier, vol. 265(C).
    11. Kashanian, Motahareh & Pishvaee, Mir Saman & Sahebi, Hadi, 2020. "Sustainable biomass portfolio sourcing plan using multi-stage stochastic programming," Energy, Elsevier, vol. 204(C).
    12. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Safaripour, Maryam & Saidi, Majid & Nodeh, Hamid Rashidi, 2023. "Synthesis and application of barium tin oxide-reduced graphene oxide nanocomposite as a highly stable heterogeneous catalyst for the biodiesel production," Renewable Energy, Elsevier, vol. 217(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).
    2. Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.
    3. Henrique Piqueiro & Reinaldo Gomes & Romão Santos & Jorge Pinho de Sousa, 2023. "Managing Disruptions in a Biomass Supply Chain: A Decision Support System Based on Simulation/Optimisation," Sustainability, MDPI, vol. 15(9), pages 1-25, May.
    4. Sadeghi Darvazeh, Saeed & Mansoori Mooseloo, Farzaneh & Gholian-Jouybari, Fatemeh & Amiri, Maghsoud & Bonakdari, Hossein & Hajiaghaei-Keshteli, Mostafa, 2024. "Data-driven robust optimization to design an integrated sustainable forest biomass-to-electricity network under disjunctive uncertainties," Applied Energy, Elsevier, vol. 356(C).
    5. Guo, Jian-Xin & Tan, Xianchun & Gu, Baihe & Zhu, Kaiwei, 2022. "Integration of supply chain management of hybrid biomass power plant with carbon capture and storage operation," Renewable Energy, Elsevier, vol. 190(C), pages 1055-1065.
    6. Yin, Xuecheng & Büyüktahtakın, İ. Esra & Patel, Bhumi P., 2023. "COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk," European Journal of Operational Research, Elsevier, vol. 304(1), pages 255-275.
    7. Fernández, Elena & Hinojosa, Yolanda & Puerto, Justo & Saldanha-da-Gama, Francisco, 2019. "New algorithmic framework for conditional value at risk: Application to stochastic fixed-charge transportation," European Journal of Operational Research, Elsevier, vol. 277(1), pages 215-226.
    8. Audrius Kabašinskas & Francesca Maggioni & Kristina Šutienė & Eimutis Valakevičius, 2019. "A multistage risk-averse stochastic programming model for personal savings accrual: the evidence from Lithuania," Annals of Operations Research, Springer, vol. 279(1), pages 43-70, August.
    9. Fattahi, Mohammad & Govindan, Kannan & Maihami, Reza, 2020. "Stochastic optimization of disruption-driven supply chain network design with a new resilience metric," International Journal of Production Economics, Elsevier, vol. 230(C).
    10. Martinez-Valencia, Lina & Garcia-Perez, Manuel & Wolcott, Michael P., 2021. "Supply chain configuration of sustainable aviation fuel: Review, challenges, and pathways for including environmental and social benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    11. Md Abu Helal & Nathaniel Anderson & Yu Wei & Matthew Thompson, 2023. "A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization," Energies, MDPI, vol. 16(3), pages 1-32, January.
    12. To, Thanh & Heleno, Miguel & Valenzuela, Alan, 2022. "Risk-constrained multi-period investment model for Distributed Energy Resources considering technology costs and regulatory uncertainties," Applied Energy, Elsevier, vol. 319(C).
    13. Blossey, Gregor & Hahn, Gerd J. & Koberstein, Achim, 2022. "Planning pharmaceutical manufacturing networks in the light of uncertain production approval times," International Journal of Production Economics, Elsevier, vol. 244(C).
    14. Mu, Yunfei & Wang, Congshan & Cao, Yan & Jia, Hongjie & Zhang, Qingzhu & Yu, Xiaodan, 2022. "A CVaR-based risk assessment method for park-level integrated energy system considering the uncertainties and correlation of energy prices," Energy, Elsevier, vol. 247(C).
    15. Islam Hassanin & Matjaz Knez, 2022. "Managing Supply Chain Activities in the Field of Energy Production Focusing on Renewables," Sustainability, MDPI, vol. 14(12), pages 1-33, June.
    16. Edgar Gutierrez-Franco & Andres Polo & Nicolas Clavijo-Buritica & Luis Rabelo, 2021. "Multi-Objective Optimization to Support the Design of a Sustainable Supply Chain for the Generation of Biofuels from Forest Waste," Sustainability, MDPI, vol. 13(14), pages 1-27, July.
    17. Albashabsheh, Nibal T. & Heier Stamm, Jessica L., 2019. "Optimization of lignocellulosic biomass-to-biofuel supply chains with mobile pelleting," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 545-562.
    18. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    19. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    20. Yu, Min Gyung & Pavlak, Gregory S., 2023. "Risk-aware sizing and transactive control of building portfolios with thermal energy storage," Applied Energy, Elsevier, vol. 332(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:200:y:2022:i:c:p:694-705. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.