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Managing congestion in supply chains via dynamic freight routing: An application in the biomass supply chain

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  • Marufuzzaman, Mohammad
  • Ekşioğlu, Sandra Duni

Abstract

This paper manages congestion in the supply chain via dynamic freight routing and using multi-modal facilities in different time periods of a year. The proposed mixed integer non-linear program (MINLP) model captures the trade-offs that exists between investment, transportation, and congestion management decisions. A linear approximation of the proposed MINLP model is then solved using a hybrid Benders-based rolling horizon algorithm. The performance of the algorithm is tested on a case study that uses data from the Southeast USA biomass supply chain network. Extensive numerical experiments provide managerial insights to manage congestion from the biomass supply chain network.

Suggested Citation

  • Marufuzzaman, Mohammad & Ekşioğlu, Sandra Duni, 2017. "Managing congestion in supply chains via dynamic freight routing: An application in the biomass supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 54-76.
    • Handle: RePEc:eee:transe:v:99:y:2017:i:c:p:54-76
    DOI: 10.1016/j.tre.2017.01.005
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    5. 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).
    6. Hugo Guzmán-Bello & Iosvani López-Díaz & Miguel Aybar-Mejía & Jose Atilio de Frias, 2022. "A Review of Trends in the Energy Use of Biomass: The Case of the Dominican Republic," Sustainability, MDPI, vol. 14(7), pages 1-27, March.
    7. Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
    8. 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.
    9. Jahani, Hamed & Gholizadeh, Hadi & Hayati, Zahra & Fazlollahtabar, Hamed, 2023. "Investment risk assessment of the biomass-to-energy supply chain using system dynamics," Renewable Energy, Elsevier, vol. 203(C), pages 554-567.
    10. Gafti, Morteza & Sabouhi, Fatemeh & Bozorgi-Amiri, Ali & Jamili, Amin, 2023. "A multi-period location-routing model for waste-to-energy supply chain: A case study," Applied Energy, Elsevier, vol. 337(C).
    11. Schmidt, Carise E. & Silva, Arinei C.L. & Darvish, Maryam & Coelho, Leandro C., 2019. "The time-dependent location-routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 293-315.
    12. Andrzej Karbowski, 2021. "Generalized Benders Decomposition Method to Solve Big Mixed-Integer Nonlinear Optimization Problems with Convex Objective and Constraints Functions," Energies, MDPI, vol. 14(20), pages 1-18, October.

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