A linear programming-based method for the network revenue management problem of air cargo

Kuan-cheng Huang*, Heng Lu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

One critical operational issue of air cargo operation faced by airlines is the control over the sales of their limited cargo space. Since American Airlines' successful implementation in the post-deregulation era, revenue management (RM) has become a common practice for the airline industry. However, unlike the air passenger operation supported by well-developed RM systems with advanced decision models, the decision process in selling air cargo space to freight forwarders is usually based on experience, without much support from optimization techniques. This study first formulates a multi-dimensional dynamic programming (DP) model to present a network RM problem for air cargo. In order to overcome the computational challenge, this study develops two linear programming (LP) based models to provide the decision support operationally suitable for airlines. In addition, this study further introduces a dynamic adjustment factor to alleviate the inaccuracy problem of the static LP models in estimating resource opportunity cost. Finally, a numerical experiment is performed to validate the applicability of the developed model and solution algorithm to the real-world problems.

Original languageEnglish
Pages (from-to)248-259
Number of pages12
JournalTransportation Research Part C: Emerging Technologies
Volume59
DOIs
StatePublished - 1 Oct 2015

Keywords

  • Air cargo
  • Demand uncertainty
  • Mathematical programming
  • Revenue management

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