IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v79y2015icp83-101.html
   My bibliography  Save this article

An inventory-based simulation model for annual-to-daily temporal freight assignment

Author

Listed:
  • Zhao, Miyuan
  • Chow, Joseph Y.J.
  • Ritchie, Stephen G.

Abstract

In the aggregate freight demand modeling literature, temporal assignment (annual to daily flows) is often oversimplified or neglected altogether. Unlike passenger flows, freight flows over the course of a year are not uniform and can vary significantly as the result of trade-offs between inventory and transportation cost management. We introduce the first temporal assignment model that explicitly considers these trade-offs for aggregate freight forecasting. A two-stage model is proposed that first decomposes aggregate annual zonal flows to firm group annual flows using a supply chain network model, which are then temporally assigned by simulating purchase order transactions throughout supply chains. Lot sizes are estimated with an Economic Order Quantity (EOQ) model and calibrated with monthly inventory data. The result is an aggregate-disaggregate-aggregate model that fits into aggregate freight forecasting models but makes use of more disaggregate logistical data. The model is illustrated with a simple replicable example, followed by a case study conducted with California statewide data to break out the distributed zonal flows into average daily volumes for network assignment. Calibration results using 2007 IMPLAN data showed a median percentage difference of simulated annual flows from FAF3 data of 2.38%, and a median percentage difference of simulated inventories from IMPLAN data of 4.85%, which suggests an excellent fit. Empirical validation results showed the model outperforms fixed factor approaches in mean value accuracy by 15–31%.

Suggested Citation

  • Zhao, Miyuan & Chow, Joseph Y.J. & Ritchie, Stephen G., 2015. "An inventory-based simulation model for annual-to-daily temporal freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 83-101.
  • Handle: RePEc:eee:transe:v:79:y:2015:i:c:p:83-101
    DOI: 10.1016/j.tre.2015.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554515000745
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2015.04.001?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. Chow, Joseph Y.J. & Ritchie, Stephen G. & Jeong, Kyungsoo, 2014. "Nonlinear inverse optimization for parameter estimation of commodity-vehicle-decoupled freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 71-91.
    2. Joseph Chow & Choon Yang & Amelia Regan, 2010. "State-of-the art of freight forecast modeling: lessons learned and the road ahead," Transportation, Springer, vol. 37(6), pages 1011-1030, November.
    3. Allen, Donald S., 1997. "A multi-sector inventory model," Journal of Economic Behavior & Organization, Elsevier, vol. 32(1), pages 55-87, January.
    4. Lovell, Michael C., 1993. "Simulating the inventory cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 21(2), pages 147-179, June.
    5. de Jong, Gerard & Ben-Akiva, Moshe, 2007. "A micro-simulation model of shipment size and transport chain choice," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 950-965, November.
    6. Nagurney, Anna & Dong, June & Zhang, Ding, 2002. "A supply chain network equilibrium model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(5), pages 281-303, September.
    7. Rieksts, Brian Q. & Ventura, Jose A., 2008. "Optimal inventory policies with two modes of freight transportation," European Journal of Operational Research, Elsevier, vol. 186(2), pages 576-585, April.
    8. Swenseth, Scott R. & Godfrey, Michael R., 2002. "Incorporating transportation costs into inventory replenishment decisions," International Journal of Production Economics, Elsevier, vol. 77(2), pages 113-130, May.
    9. Yamada, Tadashi & Imai, Koji & Nakamura, Takamasa & Taniguchi, Eiichi, 2011. "A supply chain-transport supernetwork equilibrium model with the behaviour of freight carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 887-907.
    10. Aura Reggiani & Laurie A. Schintler (ed.), 2005. "Methods and Models in Transport and Telecommunications," Advances in Spatial Science, Springer, number 978-3-540-28550-2.
    11. Harker, Patrick T. & Friesz, Terry L., 1986. "Prediction of intercity freight flows, I: Theory," Transportation Research Part B: Methodological, Elsevier, vol. 20(2), pages 139-153, April.
    12. W. J. Baumol & H. D. Vinod, 1970. "An Inventory Theoretic Model of Freight Transport Demand," Management Science, INFORMS, vol. 16(7), pages 413-421, March.
    13. Lawrence D. Burns & Randolph W. Hall & Dennis E. Blumenfeld & Carlos F. Daganzo, 1985. "Distribution Strategies that Minimize Transportation and Inventory Costs," Operations Research, INFORMS, vol. 33(3), pages 469-490, June.
    14. Harker, Patrick T. & Friesz, Terry L., 1986. "Prediction of intercity freight flows, II: Mathematical formulations," Transportation Research Part B: Methodological, Elsevier, vol. 20(2), pages 155-174, April.
    15. Sherali, Hanif D. & Park, Taehyung, 2001. "Estimation of dynamic origin-destination trip tables for a general network," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 217-235, March.
    16. Anna Nagurney, 2006. "Supply Chain Network Economics," Books, Edward Elgar Publishing, number 4242.
    17. Gernot Liedtke & Hanno Friedrich, 2012. "Generation of logistics networks in freight transportation models," Transportation, Springer, vol. 39(6), pages 1335-1351, November.
    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. 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.
    2. Di Zhang & Xinyuan Li & Chengpeng Wan & Jie Man, 2024. "A novel hybrid deep-learning framework for medium-term container throughput forecasting: an application to China’s Guangzhou, Qingdao and Shanghai hub ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(1), pages 44-73, March.
    3. Ng, Max T.M. & Hernandez, Adrian & Durango-Cohen, Pablo L. & Mahmassani, Hani S., 2024. "Trading off energy storage and payload – An analytical model for freight train configuration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    4. Davis, Haggai & Landes, Hector & Namdarpour, Farnoosh & Yang, Hai & Y. J. Chow, Joseph & Ozbay, Kaan, 2024. "Aggregate urban truck tour synthesis from public data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    5. 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.

    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. Chow, Joseph Y.J. & Ritchie, Stephen G. & Jeong, Kyungsoo, 2014. "Nonlinear inverse optimization for parameter estimation of commodity-vehicle-decoupled freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 71-91.
    2. Yamada, Tadashi & Febri, Zukhruf, 2015. "Freight transport network design using particle swarm optimisation in supply chain–transport supernetwork equilibrium," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 164-187.
    3. Mosca, Alyssa & Vidyarthi, Navneet & Satir, Ahmet, 2019. "Integrated transportation – inventory models: A review," Operations Research Perspectives, Elsevier, vol. 6(C).
    4. Nagurney, Anna & Saberi, Sara & Shukla, Shivani & Floden, Jonas, 2015. "Supply chain network competition in price and quality with multiple manufacturers and freight service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 248-267.
    5. Hensher, David A. & Teye, Collins, 2019. "Commodity interaction in freight movement models for New South Wales," Journal of Transport Geography, Elsevier, vol. 80(C).
    6. Bell, Michael G.H. & Liu, Xin & Rioult, Jeremy & Angeloudis, Panagiotis, 2013. "A cost-based maritime container assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 58-70.
    7. Baller, Reinhard & Fontaine, Pirmin & Minner, Stefan & Lai, Zhen, 2022. "Optimizing automotive inbound logistics: A mixed-integer linear programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    8. Nagurney, Anna & Shukla, Shivani & Nagurney, Ladimer S. & Saberi, Sara, 2018. "A game theory model for freight service provision security investments for high-value cargo," Economics of Transportation, Elsevier, vol. 16(C), pages 21-28.
    9. Shen, Guoqiang & Zhou, Long & Aydin, Saniye Gizem, 2020. "A multi-level spatial-temporal model for freight movement: The case of manufactured goods flows on the U.S. highway networks," Journal of Transport Geography, Elsevier, vol. 88(C).
    10. Li, Xinyan & Xie, Chi & Bao, Zhaoyao, 2022. "A multimodal multicommodity network equilibrium model with service capacity and bottleneck congestion for China-Europe containerized freight flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    11. Engebrethsen, Erna & Dauzère-Pérès, Stéphane, 2019. "Transportation mode selection in inventory models: A literature review," European Journal of Operational Research, Elsevier, vol. 279(1), pages 1-25.
    12. Ottemöller, Ole & Friedrich, Hanno, 2019. "Modelling change in supply-chain-structures and its effect on freight transport demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 23-42.
    13. Bell, Michael G.H. & Liu, Xin & Angeloudis, Panagiotis & Fonzone, Achille & Hosseinloo, Solmaz Haji, 2011. "A frequency-based maritime container assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1152-1161, September.
    14. Pani, Agnivesh & Sahu, Prasanta K. & Tavasszy, Lóránt & Mishra, Sabya, 2023. "Freight activity-travel pattern generation (FAPG) as an enhancement of freight (trip) generation modelling: Methodology and case study," Transport Policy, Elsevier, vol. 144(C), pages 34-48.
    15. Zugang Liu & Anna Nagurney, 2009. "An integrated electric power supply chain and fuel market network framework: Theoretical modeling with empirical analysis for New England," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(7), pages 600-624, October.
    16. Friesz, Terry L. & Suo, Zhong-Gui & Bernstein, David H., 1998. "A dynamic disequilibrium interregional commodity flow model," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 467-483, September.
    17. Shibasaki, Ryuichi & Ieda, Hitoshi & Watanabe, Tomihiro, 2005. "An International Container Shipping Model in East Asia and its Transferability," Research in Transportation Economics, Elsevier, vol. 13(1), pages 299-336, January.
    18. Palsule-Desai, Omkar D., 2015. "Cooperatives for fruits and vegetables in emerging countries: Rationalization and impact of decentralization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 114-140.
    19. Bachmann, Christian, 2016. "Analyzing the Infrastructure Impacts of Free Trade Agreements," Conference papers 332725, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    20. San-José, Luis A. & García-Laguna, Juan, 2009. "Optimal policy for an inventory system with backlogging and all-units discounts: Application to the composite lot size model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 808-823, February.

    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:transe:v:79:y:2015:i:c:p:83-101. 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.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.