Aviation Academy

Optimization-simulation implementations for harmonizing operations at large airports

Optimization and simulation techniques for modelling and optimizing integrated airport operations.

Project

Today’s constant air traffic growth has led to congestion problems at airports across the globe. In this project, the Amsterdam University of Applied Sciences (AUAS) has looked at ways to optimize integrated airport operations to help deal with this problem. Unlike other studies in this field of research, it takes a holistic view, and contributes by a) supporting the decisions air traffic controllers make in terms of aircraft sequencing, and b) by helping to mitigate airport congestion on the ground.

Photo: Ken Yam

Airport congestion with real-world implications

Airport congestion isn’t just an annoyance – it has real-world implications. The airspace surrounding the airport – called the terminal manoeuvring area (TMA) – is particularly congested as it tries to accommodate all traffic to and from the airport. But congestion also occurs on the ground, where air traffic inefficiencies lead to delays which are then passed on to other airports down the line. In terms of safety, congestion also increases air traffic controllers’ workload, forcing them to handle increasingly larger amounts of traffic.

Combining optimization and simulation models

This project combined optimization and simulation techniques by developing two methods aiming to improve solution robustness and feasibility. Researchers used the concept of an optimization model to identify an objective function to deal with the number of airspace conflicts and amount of capacity overload on the ground. They also used a simulation model and included random variables to represent sources of uncertainty.

Both methods were effective in improving performance. The first optimization/simulation model reduced the total number of conflicts by up to 24%, while the second optimization/simulation model reduced the total number of conflicts by up to 11%. These methods could potentially be applied to similar problems by adapting different optimization methods.

Solutions with real-world impact

Two major stakeholder groups will benefit from this study: passengers will experience more travel comfort due to smoother operations and fewer delays, while airports, airlines and air traffic controllers will achieve better use of their limited resources.

'Traditional analytical techniques can fall short when it comes to finding solutions that optimize resources at hand', says PhD student Paolo Scala. 'Our computer modelling approach is future-friendly, and helps us create robust solutions that can be applied immediately in the real world. Our use of simulations allows everybody – from aviation industry operational managers to high level decision makers – to understand inefficiencies and create real change. The result is an improvement in resource management that can drastically reduce operational costs.'

Impact on education

Modelling and Simulation (M&S) is one of the pillars within the AUAS's Aviation bachelor program, present in both the second and third years. Thesis projects related to airport capacity and the use of (M&S) techniques are also used to motivate students.

Partners

This project was conducted by PhD student Paolo Scala. It was supervised by Dr. Miguel Mujica Mota (AUAS) and Prof. Daniel Delahaye (ENAC). The AUAS supported the project by providing Paolo Scala with a four-year scholarship. The AUAS also cooperated closely with the University of Toulouse (the institution granting the PhD) and Ecole Nationale de L’Aviation Civile (ENAC) – the globally recognized institute where the research was conducted.

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Airport and Airspace Capacity research line

This project was conducted within the Airport and Airspace Capacity research line. Airport and Airspace Capacity research uses computer modelling, mathematical programming, algorithmic development and even a combination of all three to understand and improve systems at an airport or across an entire network.

Published by  Centre for Applied Research Technology 12 September 2024

Project Info

Jue Huang
Start date 01 Jan 2016
End date 07 Oct 2019

Contact

Paolo Scala