Abstract

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.

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