3.73 - Airline Fleet Composition: Analysis and Planning

Project Description

This thesis’ focus is the airline fleet composition problem, particularly in terms of its planning and modeling features. More specifically, this work investigates the best way for an airline to decide how to plan its aircraft fleet, in order to accomplish a pre-determined number of goals and to comply with the inevitable reality constraints. Whether the airline should acquire or lease the aircraft, how many aircraft models should the airline choose to compose its fleet, what would be the best fleet mix in order to minimize the airline’s costs (or maximize the airline’s revenues) and to fulfill the predicted demand, are some of the questions that this work will try to answer.

An extensive review of the existing literature in terms of fleet planning problems, in general, and airline fleet planning problems, in particular, is presented. The most relevant fleet planning optimization models are identified and classified. An analysis on the currently existing literature in terms of leasing of aircraft is also included in this work. And the major gaps existing in this research field are identified, as a starting point for the work developed.

Furthermore, the major aircraft manufacturers in the aviation market are enumerated and a description and characterization of the most relevant aircraft types is provided, focusing on its most relevant features, such as seat capacity, range and aircraft size dimensions. An analysis of the evolution throughout time of aircraft models and aviation in general is included. Additionally, this work presents a rank of the world’s largest airlines, as well as a general review on airlines’ efficiency, productivity and costs. Four airlines were chosen (American Airlines and Delta Air Lines, from the United States; and Ryanair and Lufthansa, from Europe) to be examined in terms of their fleets’ evolution. American Airlines and Delta Air Lines are two of the biggest airlines in the world, and offer a fleet mix of mainly Airbus, Boeing, and McDonnell Douglas models. In Europe, Ryanair and Lufthansa are two of the largest airlines. Ryanair currently existing fleet is an only-Boeing 737-800 (next Generation) fleet, while Lufthansa’s fleet is predominantly composed by Airbus models (although it also includes some Boeing aircraft).

Two airline fleet planning models were developed: one focused on airline long-distance operations, whereas the other model’s focal point is an airline short-distance network and fleet. For the first model, a strategic fleet planning problem faced by TAP Air Portugal, the Portuguese legacy carrier, was presented, with the aim of shedding light on the aircraft models to select, as well as on the mix of aircraft to purchase (or financially lease) and the aircraft to operationally lease in order to cope with the forecasted passenger demand between Lisbon and Brazil (TAP long-distance operations), in the year of 2020. The developed approach was based on an optimization model that can be cast in the class of two-stage stochastic integer programs. The results of the study provided clear insights on how TAP should renovate its fleet, depending on the available resources. The leasing of aircraft is an option that should definitely be taken into consideration by TAP, since it allows the carrier to deal with demand uncertainty without investing large amount of resources in the purchase of new aircraft.

Regarding the short-distance model, an integer static and deterministic optimization model was developed and applied to a TAP Europe inspired case study. The demand was considered deterministic, and the study was conducted considering a specific time period. The results of the study helped providing some understanding on how TAP could benefit by performing some changes in its short-distance fleet. The optimization model developed, integrated within an overall application methodology, proved to be a useful tool that could be used by airlines when planning their short-distance fleet.

This thesis work, in particular the two optimization models developed, can certainly contribute as a fairly helpful tool for airlines when dealing with fleet planning decisions.

Research Team


  • Joana Carreira
  • António Pais Antunes (supervisor)

Ohio State University

  • Morton O’Kelly (supervisor)
Financial Support
  • FCT
Stage of Progress
  • Finished in 2018