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

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  • Pak, K.
  • Dekker, R.

Abstract

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
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    References listed on IDEAS

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    Cited by:

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    2. Andreea Popescu & Earl Barnes & Ellis Johnson & Pinar Keskinocak, 2013. "Bid Prices When Demand Is a Mix of Individual and Batch Bookings," Transportation Science, INFORMS, vol. 47(2), pages 198-213, May.
    3. 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.
    4. 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.
    5. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    6. Masato Wada & Felipe Delgado & Bernardo K. Pagnoncelli, 2017. "A risk averse approach to the capacity allocation problem in the airline cargo industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 643-651, June.
    7. Wai Hung Wong & Anming Zhang & Yer Van Hui & Lawrence C. Leung, 2009. "Optimal Baggage-Limit Policy: Airline Passenger and Cargo Allocation," Transportation Science, INFORMS, vol. 43(3), pages 355-369, August.
    8. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    9. 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.
    10. Kannapha Amaruchkul & William L. Cooper & Diwakar Gupta, 2007. "Single-Leg Air-Cargo Revenue Management," Transportation Science, INFORMS, vol. 41(4), pages 457-469, November.
    11. Bart Riessen & Rudy R. Negenborn & Rommert Dekker, 2017. "The Cargo Fare Class Mix problem for an intermodal corridor: revenue management in synchromodal container transportation," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 634-658, December.
    12. 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.

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    More about this item

    Keywords

    cargo transportation; multi-dimensional knapsack; on-line knapsack; revenue management;
    All these keywords.

    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

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