Abstract
Revenue Management problems have been studied widely and actively in airlines for many decades, especially focusing on a seat assignment problem, a booking control problem and a dynamic pricing problem. Traditionally, most of seat revenue management problems in airlines have focused on the seat assignment and booking control for one-way flight. However, most booking requests for air travel are occurred a round-trip basis. In the traditional model, the round trip itinerary was divided into two one-way itineraries independently and the seat assignment problem based on the each itinerary demand has been studied individually. The traditional RM approach is no longer suitable for managing seat assignments and booking controls on round trip itineraries. Furthermore, it is common to travel in small groups rather than individuals, and airlines may consider offering discount fares (quantity discount fares) for such groups which can be found in many retail shopping and recognized to induce more demand. In this paper, we deal with the itinerary based revenue management problem focusing on the seat assignment and booking control with quantity discount fares. Our problem has not been studied effectively in the previous researches. We will suggest an optimization model and a greedy-type heuristic to determine the seat assignment for our complex problem. Based on the seat assignment solution, we will also suggest an effective booking control method to decide the acceptance or the rejection for a seat request. Even though the seat assignment model can be modeled as a probabilistic Integer programming model, we show it can be transformed to the simple Integer programming model by applying Linear Approximation technique. For itinerary-based booking control, we also suggest an effective mixed nesting control method. As a result of the simulation, we can find that our methods make more revenue gains (2.2%~5.1%) compared to the modified traditional ones. Expecially, when the demand is relatively high, the revenue gain is larger. In this study, we suggest some effective approach to solve the problem of seat assignment and booking allocation for itinerary-based demand with small groups, which has not been considered effectively so far. To enhance the applicability of our model in practice, it needs to develop more comprehensive models including diversions, no-shows and behavioral factors in air travelers.
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