Spring 2008 Seminar Series

DATE: March 13, 2008
LOCATION: E40-298
TIME: 4:15pm
Reception immediately following in the ORC ConferenceRoom, E40-106

SPEAKER:
Michael O. Ball

TITLE
Robust Revenue Management with Limited Demand Information

ABSTRACT
In this talk we summarize a body of work that has addressed revenue management problems using the perspective of competitive analysis of online algorithms. Specifically, we consider the classical multiple-fare, single resource (leg) problem. Our approach provides a guaranteed performance level under all possible input sequences. Initial work on this problem placed no restrictions on the input sequences. More recent work has assumed that limited demand information is available in the form of lower and/or upper bounds on the demand (number of orders) in each fare class. This leads to a model with certain restrictions on the possible input sequences. We consider both relative and absolute regret performance criteria and derive the best possible policies under the various models we analyze. The optimal policies have the form of nested protection levels. Our analysis covers both static policies, whose booking limits remain constant throughout the booking horizon, and dynamic policies, whose booking limits may be adjusted at any time based on the history of bookings. Very recent work has 1) integrated in treatment of the overbooking problem and 2) considered a multi-period variant under which demand bounds vary by time period. We provide extensive computational experiments and compare our methods to existing ones. The results of the experiments demonstrate the effectiveness of these new robust methods.

Co-authors: Itir Karaesmen, Huina Gao, Yingjie Lan