IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v121y2019icp63-83.html
   My bibliography  Save this article

Entropy-based freight tour synthesis and the role of traffic count sampling

Author

Listed:
  • Gonzalez-Calderon, Carlos A.
  • Holguín-Veras, José

Abstract

This paper describes a Freight Tour Synthesis (FTS) model designed to infer aggregate pick-up/delivery tour flows using secondary data, such as traffic counts and zonal freight trip generation estimates. The formulation combines an entropy maximization demand model together with the secondary data constraints. The entropy function is maximized subject to the system constraints to estimate the most likely freight tours that best fit the secondary data. To assess the role of traffic counts, the authors design four different heuristics to identify the locations of the traffic counts to be used in the estimation, and assess their performance under different scenarios of traffic counts availability.

Suggested Citation

  • Gonzalez-Calderon, Carlos A. & Holguín-Veras, José, 2019. "Entropy-based freight tour synthesis and the role of traffic count sampling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 63-83.
    • Handle: RePEc:eee:transe:v:121:y:2019:i:c:p:63-83
    DOI: 10.1016/j.tre.2017.10.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554516304951
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2017.10.010?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. José Holguín-Veras & Gopal Patil, 2008. "A Multicommodity Integrated Freight Origin–destination Synthesis Model," Networks and Spatial Economics, Springer, vol. 8(2), pages 309-326, September.
    2. Van Zuylen, Henk J. & Willumsen, Luis G., 1980. "The most likely trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 281-293, September.
    3. 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.
    4. Gédéon, Christine & Florian, Michael & Crainic, Teodor G., 1993. "Determining origin-destination matrices and optimal multiproduct flows for freight transportation over multimodal networks," Transportation Research Part B: Methodological, Elsevier, vol. 27(5), pages 351-368, October.
    5. Jacques Guélat & Michael Florian & Teodor Gabriel Crainic, 1990. "A Multimode Multiproduct Network Assignment Model for Strategic Planning of Freight Flows," Transportation Science, INFORMS, vol. 24(1), pages 25-39, February.
    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. Holguín-Veras, José & Kalahasthi, Lokesh & Ramirez-Rios, Diana G., 2021. "Service trip attraction in commercial establishments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    2. Thoen, Sebastiaan & Tavasszy, Lóránt & de Bok, Michiel & Correia, Goncalo & van Duin, Ron, 2020. "Descriptive modeling of freight tour formation: A shipment-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    3. Malik, Leeza & Tiwari, Geetam & Biswas, Udayin & Woxenius, Johan, 2021. "Estimating urban freight flow using limited data: The case of Delhi, India," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    4. Regal, Andrés & Gonzalez-Feliu, Jesús & Rodriguez, Michelle, 2023. "A spatio-functional logistics profile clustering analysis method for metropolitan areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    5. Diana P. Moreno-Palacio & Carlos A. Gonzalez-Calderon & John Jairo Posada-Henao & Hector Lopez-Ospina & Jhan Kevin Gil-Marin, 2022. "Entropy-Based Transit Tour Synthesis Using Fuzzy Logic," Sustainability, MDPI, vol. 14(21), pages 1-25, November.
    6. David A. Hensher & Edward Wei & Wen Liu & Loan Ho & Chinh Ho, 2023. "Development of a practical aggregate spatial road freight modal demand model system for truck and commodity movements with an application of a distance-based charging regime," Transportation, Springer, vol. 50(3), pages 1031-1071, June.
    7. Kalahasthi, Lokesh & Holguín-Veras, José & Yushimito, Wilfredo F., 2022. "A freight origin-destination synthesis model with mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(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. Kalahasthi, Lokesh & Holguín-Veras, José & Yushimito, Wilfredo F., 2022. "A freight origin-destination synthesis model with mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    2. 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.
    3. Malik, Leeza & Tiwari, Geetam & Biswas, Udayin & Woxenius, Johan, 2021. "Estimating urban freight flow using limited data: The case of Delhi, India," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    4. Cheah, Lynette & Mepparambath, Rakhi Manohar & Ricart Surribas, Gabriella Marie, 2021. "Freight trips generated at retail malls in dense urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 118-131.
    5. Jansuwan, Sarawut & Ryu, Seungkyu & Chen, Anthony, 2017. "A two-stage approach for estimating a statewide truck trip table," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 274-292.
    6. Zhao, Dongfang & Balusu, Suryaprasanna Kumar & Sheela, Parvathy Vinod & Li, Xiaopeng & Pinjari, Abdul Rawoof & Eluru, Naveen, 2020. "Weight-categorized truck flow estimation: A data-fusion approach and a Florida case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. Casavant, Ken & Jessup, Eric, 2005. "What Makes them Viable? Determining the Attributes that Offer Potential Viability to Inter-Modal Truck-Rail Facilities in Washington State," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208221, Transportation Research Forum.
    8. Abareshi, Maryam & Zaferanieh, Mehdi, 2019. "A bi-level capacitated P-median facility location problem with the most likely allocation solution," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 1-20.
    9. Cho, Joongkoo & Hu, Weihong, 2013. "Network-Based Simulation of Air Pollution Emissions Associated with Truck Operations," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 52(3).
    10. 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.
    11. Haghani, Ali & Oh, Sei-Chang, 1996. "Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 231-250, May.
    12. Shen, Wei & Wynter, Laura, 2012. "A new one-level convex optimization approach for estimating origin–destination demand," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1535-1555.
    13. M. Bierlaire & F. Crittin, 2004. "An Efficient Algorithm for Real-Time Estimation and Prediction of Dynamic OD Tables," Operations Research, INFORMS, vol. 52(1), pages 116-127, February.
    14. Furini, Fabio & Persiani, Carlo Alfredo & Toth, Paolo, 2016. "The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 38-55.
    15. Hensher, David A. & Teye, Collins, 2019. "Commodity interaction in freight movement models for New South Wales," Journal of Transport Geography, Elsevier, vol. 80(C).
    16. Van Der Zijpp, Nanne J. & De Romph, Erik, 1997. "A dynamic traffic forecasting application on the Amsterdam beltway," International Journal of Forecasting, Elsevier, vol. 13(1), pages 87-103, March.
    17. Menon, Aditya Krishna & Cai, Chen & Wang, Weihong & Wen, Tao & Chen, Fang, 2015. "Fine-grained OD estimation with automated zoning and sparsity regularisation," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 150-172.
    18. Xiaoxuan Wei & Meng Ye & Liang Yuan & Wei Bi & Weisheng Lu, 2022. "Analyzing the Freight Characteristics and Carbon Emission of Construction Waste Hauling Trucks: Big Data Analytics of Hong Kong," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    19. Yu Nie & H. Zhang, 2010. "A Relaxation Approach for Estimating Origin–Destination Trip Tables," Networks and Spatial Economics, Springer, vol. 10(1), pages 147-172, March.
    20. Krisztin, Tamás, 2018. "Semi-parametric spatial autoregressive models in freight generation modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 121-143.

    More about this item

    Statistics

    Access and download statistics

    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:121:y:2019:i:c:p:63-83. 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.