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Principles of micro-behavior commodity transport modeling

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  • Liedtke, Gernot

Abstract

This paper presents an agent-based approach to commodity transport modeling. It assesses the effects of behavior-oriented transport policy measures while taking complex logistics reaction patterns into account. It is structured by modules describing company generation, supplier choice, shipment-size choice, carrier choice and tour construction. The behavior of individual actors is simulated using normative logistics models and accumulated market knowledge. Using a bottom-up approach, shippers and carriers interact through simulated auctions of transport contracts resulting in the generation of tours. Simulations using the model prototype INTERLOG calibrated with German data demonstrate the capabilities and limitations of this approach.

Suggested Citation

  • Liedtke, Gernot, 2009. "Principles of micro-behavior commodity transport modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(5), pages 795-809, September.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:5:p:795-809
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    Cited by:

    1. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    2. Marcucci, Edoardo & Le Pira, Michela & Gatta, Valerio & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro, 2017. "Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders’ preferences and interaction effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 69-86.
    3. Takanori Sakai & B. K. Bhavathrathan & André Alho & Tetsuro Hyodo & Moshe Ben-Akiva, 2020. "Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model," Transportation, Springer, vol. 47(2), pages 997-1025, April.
    4. Baindur, Deepak & Viegas, José Manuel, 2011. "An agent based model concept for assessing modal share in inter-regional freight transport markets," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1093-1105.
    5. Mommens, Koen & Buldeo Rai, Heleen & van Lier, Tom & Macharis, Cathy, 2021. "Delivery to homes or collection points? A sustainability analysis for urban, urbanised and rural areas in Belgium," Journal of Transport Geography, Elsevier, vol. 94(C).
    6. Reis, Vasco, 2014. "Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 100-120.
    7. Gernot Liedtke & Hanno Friedrich, 2012. "Generation of logistics networks in freight transportation models," Transportation, Springer, vol. 39(6), pages 1335-1351, November.
    8. Johan Joubert & Kay Axhausen, 2013. "A complex network approach to understand commercial vehicle movement," Transportation, Springer, vol. 40(3), pages 729-750, May.
    9. Theodore Tsekeris & Klimis Vogiatzoglou, 2011. "Spatial agent-based modeling of household and firm location with endogenous transport costs," Netnomics, Springer, vol. 12(2), pages 77-98, July.
    10. Edoardo Marcucci, 2013. "Logistics Managers' Stated Preferences For Freight Service Attributes: A Comparative Research Method Analysis," Working Papers 0213, CREI Università degli Studi Roma Tre, revised 2013.
    11. Patricio Gallardo & Rua Murray & Susan Krumdieck, 2021. "A Sequential Optimization-Simulation Approach for Planning the Transition to the Low Carbon Freight System with Case Study in the North Island of New Zealand," Energies, MDPI, vol. 14(11), pages 1-24, June.
    12. Sánchez-Díaz, Iván & Holguín-Veras, José & Ban, Xuegang (Jeff), 2015. "A time-dependent freight tour synthesis model," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 144-168.
    13. Crainic, Teodor Gabriel & Perboli, Guido & Rosano, Mariangela, 2018. "Simulation of intermodal freight transportation systems: a taxonomy," European Journal of Operational Research, Elsevier, vol. 270(2), pages 401-418.
    14. Gerard Jong & Inge Vierth & Lori Tavasszy & Moshe Ben-Akiva, 2013. "Recent developments in national and international freight transport models within Europe," Transportation, Springer, vol. 40(2), pages 347-371, February.
    15. de Bok, Michiel & Tavasszy, Lóránt & Sebastiaan Thoen,, 2022. "Application of an empirical multi-agent model for urban goods transport to analyze impacts of zero emission zones in The Netherlands," Transport Policy, Elsevier, vol. 124(C), pages 119-127.
    16. Carrillo Murillo, David Guillermo & Liedtke, Gernot, 2013. "A model for the formation of colloidal structures in freight transportation: The case of hinterland terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 55-70.
    17. Tavasszy, Lóránt A., 2020. "Predicting the effects of logistics innovations on freight systems: Directions for research," Transport Policy, Elsevier, vol. 86(C), pages 1-6.
    18. Jensen, Anders Fjendbo & Thorhauge, Mikkel & de Jong, Gerard & Rich, Jeppe & Dekker, Thijs & Johnson, Daniel & Cabral, Manuel Ojeda & Bates, John & Nielsen, Otto Anker, 2019. "A disaggregate freight transport chain choice model for Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 43-62.
    19. Balster, Andreas & Friedrich, Hanno, 2019. "Dynamic freight flow modelling for risk evaluation in food supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 4-22.
    20. Megersa Abate & Inge Vierth & Rune Karlsson & Gerard Jong & Jaap Baak, 2019. "A disaggregate stochastic freight transport model for Sweden," Transportation, Springer, vol. 46(3), pages 671-696, June.
    21. Theodore Tsekeris & Klimis Vogiatzoglou & Stelios Bekiros, 2011. "Multi-Regional Agent-Based Modeling of Household and Firm Location Choices with Endogenous Transport Costs," ERSA conference papers ersa10p479, European Regional Science Association.

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