Integrated Flight Scheduling and Fleet Assignment Under Airport Congestion

Abstract

Airport congestion is a major cause for the large delays that currently affect the air transport industry. These delays have huge cost implications—for the U.S. economy these costs were estimated at $32.9 billion in 2007. In this paper, we present a mixed-integer linear optimization model aimed at assisting airlines in the making of integrated flight scheduling and fleet assignment decisions that take aircraft and passenger delay costs explicitly into account. The objective of the model is to maximize the expected profits of an airline that faces a given origin/destination-based travel demand and operates in congested, slot-constrained airports. Both airline competition and airline cooperation are dealt with in the model, though in a simplified manner. The model was applied to a case study involving the main network of TAP Portugal, which comprises 31 airports and 100 daily flight legs. The results obtained through the model suggest that the Portuguese legacy carrier can improve their expected profits significantly, while diminishing the total number of flights and slightly increasing the passengers' average connecting time. The calculation effort involved in the application of the model even on a desktop computer is small enough to allow its real-time utilization in International Air Transport Association scheduling conferences. These findings clearly indicate that the model is a significant addition to the airline planning toolbox.