Revenue Management in a Dynamic Network Environment

Dimitris Bertsimas () and Ioana Popescu ()
Additional contact information
Dimitris Bertsimas: Sloan School of Management, MIT, Cambridge, Massachusetts 02139
Ioana Popescu: INSEAD, Fontainebleau Cedex 77305, France

Transportation Science, 2003, vol. 37, issue 3, 257-277

Abstract: We investigate dynamic policies for allocating scarce inventory to stochastic demand for multiple fare classes, in a network environment so as to maximize total expected revenues. Typical applications include sequential reservations for an airline network, hotel, or car rental service. We propose and analyze a new algorithm based on approximate dynamic programming, both theoretically and computationally. This algorithm uses adaptive, nonadditive bid prices from a linear programming relaxation. We provide computational results that give insight into the performance of the new algorithm and the widely used bid-price control, for several networks and demand scenarios. We extend the proposed algorithm to handle cancellations and no-shows by incorporating oversales decisions in the underlying linear programming formulation. We report encouraging computational results that show that the new algorithm leads to higher revenues and more robust performance than bid-price control.

Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (75)

Downloads: (external link)
http://dx.doi.org/10.1287/trsc.37.3.257.16047 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:37:y:2003:i:3:p:257-277

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().