Revenue management: models and methods
Proceedings of the 40th Conference on Winter Simulation
Toward Robust Revenue Management: Competitive Analysis of Online Booking
Operations Research
Robust Controls for Network Revenue Management
Manufacturing & Service Operations Management
Expert Systems with Applications: An International Journal
Fully Distribution-Free Profit Maximization: The Inventory Management Case
Mathematics of Operations Research
Regret in Overbooking and Fare-Class Allocation for Single Leg
Manufacturing & Service Operations Management
Revenue management: models and methods
Winter Simulation Conference
On the structural properties of a discrete-time single product revenue management problem
Operations Research Letters
Online lot-sizing problems with ordering, holding and shortage costs
Operations Research Letters
Markdown Pricing with Unknown Fraction of Strategic Customers
Manufacturing & Service Operations Management
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In this paper, we consider the classical multifare, single-resource (leg) problem in revenue management for the case where demand information is limited. Our approach employs a competitive analysis, which guarantees a certain performance level under all possible demand scenarios. The only information required about the demand for each fare class is lower and upper bounds. We consider both competitive ratio and absolute regret performance criteria. For both performance criteria, we derive the best possible static policies, which employ booking limits that remain constant throughout the booking horizon. The optimal policies have the form of nested booking limits. Dynamic policies, which employ booking limits that may be adjusted at any time based on the history of bookings, are also obtained. 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.