Optimization-simulation implementations for harmonizing operations at large airports
Optimization and simulation techniques for modelling and optimizing integrated airport operations.
ProjectToday’s constant air traffic growth has led to congestion problems at airports across the globe. This project looks 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.
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 to improve robustness and feasibility
This project combined optimization and simulation techniques by developing two methods aiming to improve solution robustness and feasibility. We 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. We 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.”
Results and publications
The project was run as part of a PhD track. The results were published in a PhD thesis as well as in a variety of publications for International Scientific Journals and Conferences:
Scala, P., Mujica, M., Ma, J., Delahaye, D (accepted). Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management. IEEE Transactions on Intelligent Transportation Systems. https://ieeexplore.ieee.org/document/8755486.
Ma, J., Delahaye, D., Sbihi, M., Scala, P., Mujica, M. (2019). Integrated optimization of terminal maneuvering area and airport at the macroscopic level. Transportation Research Part C, Vol. 98, pp. 338-357. https://www.sciencedirect.com/science/article/pii/S0968090X18302754
Mujica, M., Scala, P., Delahaye, D (2017). Improving Airport Performance Through a Model‐Based Analysis and Optimization Approach. New Applications in Logistics, Industrial and Aeronautical Practice, Mujica Mota and De La Mota Eds., Springer. https://link.springer.com/chapter/10.1007/978-3-319-55810-3_4
Mujica, M., Scala, P., Delahaye, D (2017). Applied Simulation and Optimization 2, New Applications in Logistics, Industrial and Aeronautical Practice, Mujica Mota and De La Mota Eds., Springer. https://link.springer.com/chapter/10.1007/978-3-319-55810-3_4
Scala, P., Mujica, M., Delahaye, D., Ma, J (2019). A Generic Framework for Modeling Airport Operations At a Macroscopic Level. Winter Simulation Congress, Maryland, USA. https://ieeexplore.ieee.org/document/9004865
Scala, P., Mujica, M., Wu, C.L., Delahaye, D. (2018). SIM-OPT IN THE LOOP: ALGORITHMIC FRAMEWORK FOR SOLVING AIRPORT CAPACITY PROBLEMS. Winter Simulation Congress, Gothenburg, Sweden. https://ieeexplore.ieee.org/document/8632531
Ma, J., Delahaye, D., Sbihi, M., Scala, P. (2018) Integrated Optimization of Arrival, Departure, and Surface Operations. International Conference for Research in Air Transportation, Barcelona, Spain. https://hal-enac.archives-ouvertes.fr/hal-01823188/document
Scala, P., Mujica, M., Delahaye, D. (2017). A Down To Earth Solution: Applying a robust simulation-optimization approach to resolve aviation problems. Winter Simulation Congress, Las Vegas, Nevada, USA. https://ieeexplore.ieee.org/document/8247989
Ma, J., Delahaye, D., Sbihi, M., Scala, P., Mujica, M. (2017). A study of Tradeoffs in Airport Coordinated Surface Operations. EIWAC 2017, Tokyo, Japan. https://hal-enac.archives-ouvertes.fr/hal-01637959/document
Scala, P., Mujica, M., Delahaye, D. (2016). NO MORE CONFLICTS: THE DEVELOPMENT OF A GENERIC AIRPORT MODEL IN A SEQUENCE OPTIMIZATION FRAMEWORK. EMSS 2016, Larnaca, Cyprus. https://pure.hva.nl/ws/files/5733521/EMSS_FULL_PAPER_SCALA_MUJICA_DELAHAYE.pdf
Scala, P., Mujica, M., Delahaye, D. (2016). Implementation of an Optimization and Simulation-Based Approach for Detecting and Resolving Conflicts at Airports. EUROSIM 2016, Oulu, Finland. http://www.ep.liu.se/ecp/142/037/ecp17142037.pdf
Mujica, M., Scala, P., Delahaye, D. (2015). Methodology for Assessing and Optimizing Operation Performance in Airport Systems. EIWAC 2015, Tokyo, Japan. https://hal.archives-ouvertes.fr/hal-01280639
Partners
This project was conducted within the Airport and Airspace Capacity lectorate by PhD student Paolo Scala. It was supervised by Dr. Miguel Mujica Mota (HvA) and Prof. Daniel Delahaye (ENAC). The HvA supported the project by providing Paolo Scala with a four-year scholarship. The HvA 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. ENAC is the leading institute in Europe in terms of aviation, offering a variety of different opportunities such as pilot and air traffic controller training and several Master of Sciences degrees. The roles of these partners were to support the enrolment within their PhD program and to supervise the research.
Impact on education
Modelling and Simulation (M&S) is one of the pillars within the HvA’s Aviation Academy Bachelor program curricula, 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.
Lectorate Airport and Airspace Capacity
This project was conducted within the Airport and Airspace Capacity lectorate. 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.
