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A freight transport optimization model for integrated network, service, and policy design

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  • Zhang, M.
  • Janic, M.
  • Tavasszy, L.A.

Abstract

This paper presents a freight transport optimization model that simultaneously incorporates multimodal infrastructure, hub-based service network structures, and the various design objectives of multiple actors. The model has been calibrated and validated using real-life data from the case study of hinterland container transport of the Netherlands, where CO2 pricing, terminal network configuration, and hub-service networks are chosen as the design measures. Policy packages combining multiple types of policies show better network performance as compared with the optimal performance resulting from a single policy type. This illustrates the value of incorporating multiple types of policies simultaneously in freight transport optimization.

Suggested Citation

  • Zhang, M. & Janic, M. & Tavasszy, L.A., 2015. "A freight transport optimization model for integrated network, service, and policy design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 61-76.
    • Handle: RePEc:eee:transe:v:77:y:2015:i:c:p:61-76
    DOI: 10.1016/j.tre.2015.02.013
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    Cited by:

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    7. Stephen Okyere & Jiaqi Yang & Charles Anum Adams, 2022. "Optimizing the Sustainable Multimodal Freight Transport and Logistics System Based on the Genetic Algorithm," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
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    14. Gupta, Dipti & Dhar, Subash, 2022. "Exploring the freight transportation transitions for mitigation and development pathways of India," Transport Policy, Elsevier, vol. 129(C), pages 156-175.
    15. Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2021. "Solving a stochastic inland waterway port management problem using a parallelized hybrid decomposition algorithm," Omega, Elsevier, vol. 102(C).
    16. Zhang, X. & Liu, X., 2022. "A two-stage robust model for express service network design with surging demand," European Journal of Operational Research, Elsevier, vol. 299(1), pages 154-167.
    17. Vitalii Naumov & Olha Shulika & Oleksandra Orda & Hanna Vasiutina & Marek Bauer & Myroslav Oliskevych, 2022. "Shaping the Optimal Technology for Servicing the Long-Distance Deliveries of Packaged Cargo by Road Transport," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    18. Edward Kim, M. & Schonfeld, Paul & Roche, Austin & Raleigh, Chelsie, 2022. "Optimal service zones and frequencies for flexible-route freight deliveries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 182-199.
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    21. Melinda Timea Fülöp & Miklós Gubán & György Kovács & Mihály Avornicului, 2021. "Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity," Energies, MDPI, vol. 14(10), pages 1-22, May.
    22. Adil Baykasoğlu & Nurhan Dudaklı & Kemal Subulan & A. Serdar Taşan, 2022. "An integrated fleet planning model with empty vehicle repositioning for an intermodal transportation system," Operational Research, Springer, vol. 22(3), pages 2063-2098, July.
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    24. Archetti, Claudia & Peirano, Lorenzo & Speranza, M. Grazia, 2022. "Optimization in multimodal freight transportation problems: A Survey," European Journal of Operational Research, Elsevier, vol. 299(1), pages 1-20.

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