Robust fleet planning under stochastic demand

Master thesis (2016)

Authors

Contributors

B.F. Santos (mentor)
J.P. Clarke (mentor)
Department
Air Transport and Operations (Aerospace Engineering) (TU Delft)
Copyright: © 2016 Sa, C.A.A.
Optimization Airline fleet planning Stochastic demand
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Published Date

27-05-2016

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Faculty

Aerospace Engineering

Department

Air Transport and Operations

Abstract

The research objective of this thesis is to develop an innovative airline fleet planning concept that is capable to consider the long-term stochastic nature of air travel demand while generating meaningful results in reasonable computation times. The proposed methodology aims to identify robust fleets, in terms of profit generating capability across a long-term planning horizon under stochastic demand, through the adoption of a portfolio of fleets (each of different size or composition) and a three-step modeling framework. The three models involve the simulation and sampling of stochastic demand using the mean reverting Ornstein-Uhlenbeck process, iteration over an optimization model that optimally allocates each fleet from the portfolio given the demand sample values, and a scenario generation model that generates scenarios across the planning horizon. A case study is presented and serves as proof of concept.