IDEAS home Printed from https://ideas.repec.org/h/spr/lnechp/978-3-540-92944-4_11.html
   My bibliography  Save this book chapter

Modeling the Pre Auction Stage The Truckload Case

In: Innovations in Distribution Logistics

Author

Listed:
  • Gianfranco Guastaroba

    (Department of Quantitative Methods)

  • Renata Mansini

    (Department of Electronics for Automation)

  • M Grazia Speranza

    (Department of Quantitative Methods)

Abstract

Summary In transportation service procurement, shipper and carriers cost functions for serving a pair of origin-destination points, usually called lanes, are highly dependent on the opportunity to serve neighboring lanes. Traditional single-item auctions do not allow to capture this type of preferences. On the contrary, they are perfectly modeled in combinatorial auctions where bids on bundles of items are allowed. In transportation service procurement the management of a combinatorial auction can be seen as a three-stage process. Each stage involves several complex decision making problems. All such problems have relevant practical implications but only some of them have received attention in the literature. In the present paper we focus on the pre-auction stage for transportation procurement. In particular, we analyze the problem of a shipper who has to decide between undertaking and/or outsourcing (through an auction) his transportation requests. The problem has never been analyzed before.We propose two different models for the problem in the truckload case and provide their computational comparison on randomly generated instances.

Suggested Citation

  • Gianfranco Guastaroba & Renata Mansini & M Grazia Speranza, 2009. "Modeling the Pre Auction Stage The Truckload Case," Lecture Notes in Economics and Mathematical Systems, in: Jo A.E.E. Nunen & M. Grazia Speranza & Luca Bertazzi (ed.), Innovations in Distribution Logistics, chapter 11, pages 219-233, Springer.
  • Handle: RePEc:spr:lnechp:978-3-540-92944-4_11
    DOI: 10.1007/978-3-540-92944-4_11
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Acocella, Angela & Caplice, Chris & Sheffi, Yossi, 2020. "Elephants or goldfish?: An empirical analysis of carrier reciprocity in dynamic freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    2. Ávila, Thais & Corberán, Ángel & Plana, Isaac & Sanchis, José M., 2016. "A branch-and-cut algorithm for the profitable windy rural postman problem," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1092-1101.
    3. Colombi, Marco & Mansini, Renata, 2014. "New results for the Directed Profitable Rural Postman Problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 760-773.
    4. Yang, Fang & Huang, Yao-Huei, 2020. "Linearization technique with superior expressions for centralized planning problem with discount policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    5. Triki, Chefi & Oprea, Simona & Beraldi, Patriza & Crainic, Teodor Gabriel, 2014. "The stochastic bid generation problem in combinatorial transportation auctions," European Journal of Operational Research, Elsevier, vol. 236(3), pages 991-999.
    6. Hammami, Farouk & Rekik, Monia & Coelho, Leandro C., 2021. "Exact and hybrid heuristic methods to solve the combinatorial bid construction problem with stochastic prices in truckload transportation services procurement auctions," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 204-229.

    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:spr:lnechp:978-3-540-92944-4_11. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.