Developing an Overbooking Fuzzy-Based Optimisation Model for Multi-Leg Flights

Overbooking is an important revenue management strategy that is currently used in many industries including airline industry. Briefly, overbooking lets airlines to mitigate the risk of flying with empty seats. However, identifying an overbooking level is a complicated task due to the uncertainties associated with the external factors that affect the booking process fundamentally. There have been many methods proposed for overbooking problem on a single-leg flight, yet few studies have been conducted on airline networks. Although, overbooking problem can be handled at the single-leg level in practice, considering the problem as a network revenue management problem can be more profitable for the airlines due to the fact that seat allocation in one leg affects other legs in the network. In this paper, a fuzzy linear programming model is proposed for the overbooking optimisation problem in multi-leg flights with multiple fare-classes. Unlike the majority of the previous studies, the uncertainties related to demand are addressed by defining the demand as fuzzy numbers. Our main aim is to propose an optimisation method that maximises the overall revenue of the flight network by minimising the number of empty seats and the number of denied passengers. Moreover, we strive to show that the proposed model can be used as a decision support tool by the airline revenue management analysts or the decision makers to assist the process of determining booking limits for different flights in airline networks. We expect to test the proposed method for different scenarios and upon successful completion of this research we will investigate the advantages of using fuzzy theory in airline network overbooking problem.