Robust Controls for Network Revenue Management

Georgia Perakis () and Guillaume Roels ()
Additional contact information
Georgia Perakis: Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
Guillaume Roels: Anderson School of Management, University of California, Los Angeles, California 90095

Manufacturing & Service Operations Management, 2010, vol. 12, issue 1, pages 56-76

Abstract: Revenue management models traditionally assume that future demand is unknown but can be described by a stochastic process or a probability distribution. Demand is, however, often difficult to characterize, especially in new or nonstationary markets. In this paper, we develop robust formulations for the capacity allocation problem in revenue management using the maximin and the minimax regret criteria under general polyhedral uncertainty sets. Our approach encompasses the following open-loop controls: partitioned booking limits, nested booking limits, displacement-adjusted virtual nesting, and fixed bid prices. In specific problem instances, we show that a booking policy of the type of displacement-adjusted virtual nesting is robust, both from maximin and minimax regret perspectives. Our numerical analysis reveals that the minimax regret controls perform very well on average, despite their worst-case focus, and outperform the traditional controls when demand is correlated or censored. In particular, on real large-scale problem sets, the minimax regret approach outperforms by up to 2% the traditional heuristics. The maximin controls are more conservative but have the merit of being associated with a minimum revenue guarantee. Our models are scalable to solve practical problems because they combine efficient (exact or heuristic) solution methods with very modest data requirements.

Keywords: revenue management; yield management; network; robust optimization; regret (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://dx.doi.org/10.1287/msom.1080.0252 (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: http://EconPapers.repec.org/RePEc:inm:ormsom:v:12:y:2010:i:1:p:56-76

Access Statistics for this article

More articles in Manufacturing & Service Operations Management from INFORMS
Contact information at EDIRC.
Series data maintained by Mirko Janc ().