IDEAS home Printed from
   My bibliography  Save this paper

Cargo Revenue Management: Bid-Prices for a 0-1 Multi Knapsack Problem


  • Pak, K.
  • Dekker, R.


Revenue management is the practice of selecting those customers that generate the maximum revenue from a fixed and perishable capacity. Cargo revenue management differs from the well-known passenger revenue management problem by the fact that its capacity constraint is 2-dimensional, i.e. weight and volume, and that the weight, volume and profit of each booking request are random and continuous variables. This leads to a multi-dimensional on-line knapsack problem. We show that a bid-price acceptance policy is asymptotically optimal if demand and capacity increase proportionally and the bid-prices are set correctly. We provide a heuristic to set the bid-prices based on a greedy algorithm for the multi-knapsack problem proposed by Rinnooy Kan et al. (1993). A test case shows that these bid-prices perform better than the traditional LP-based bid-prices that do not perform well at all for this problem.

Suggested Citation

  • Pak, K. & Dekker, R., 2004. "Cargo Revenue Management: Bid-Prices for a 0-1 Multi Knapsack Problem," ERIM Report Series Research in Management ERS-2004-055-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:1449

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    2. Jason D. Papastavrou & Srikanth Rajagopalan & Anton J. Kleywegt, 1996. "The Dynamic and Stochastic Knapsack Problem with Deadlines," Management Science, INFORMS, vol. 42(12), pages 1706-1718, December.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. van Riessen, B. & Negenborn, R.R. & Dekker, R., 2016. "Real-time Container Transport Planning with Decision Trees based on Offline Obtained Optimal Solutions," Econometric Institute Research Papers EI2016-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Luo, Sirong & Çakany?ld?r?m, Metin & Kasilingam, Raja G., 2009. "Two-dimensional cargo overbooking models," European Journal of Operational Research, Elsevier, vol. 197(3), pages 862-883, September.
    3. Han, Dong Ling & Tang, Loon Ching & Huang, Huei Chuen, 2010. "A Markov model for single-leg air cargo revenue management under a bid-price policy," European Journal of Operational Research, Elsevier, vol. 200(3), pages 800-811, February.
    4. Lin, Danping & Lee, Carman Ka Man & Yang, Jilin, 2017. "Air cargo revenue management under buy-back policy," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 53-63.

    More about this item


    cargo transportation; multi-dimensional knapsack; on-line knapsack; revenue management;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics


    Access and download statistics


    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:ems:eureri:1449. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RePub). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.