Flexible Arrival & Departure Runway Allocation Using Mixed-Integer Linear Programming

Abstract

Runway capacity of a complex runways system can be limited by several factors. Currently, the runway usage at Amsterdam Airport Schiphol (AAS) is described by a preference list established by multiple stakeholders. It makes an important trade-off between minimizing noise exposure to the environment and maximizing capacity. The existing model does not take into account fuel burn and the ensued emissions for the current and future demand in flights. This study tries to address this issue. A model has been developed using Mixed-Integer Linear Programming (MILP) by which flights can be allocated to runways, while optimizing for fuel and noise. The research has the following research question: Can fuel burn be significantly reduced for aircraft operating at Amsterdam Airport by utilizing a novel flexible arrival and departure runway allocation model, using a predefined set of variables and rules, accounting for noise annoyance, runway capacity and the current and future demand of flights? The runway allocation model developed for this study is able to assign aircraft to runways based upon an optimization trade-off between fuel usage and noise exposure to the environment. Selecting a shorter flight- or taxi route may result in lower fuel burn and emissions, while separation- and noise regulations are maintained. A multitude of scenarios is simulated using the allocation model. Different runway configurations are tested. Additionally, different peak moments varying during the day are compared to see when flexible allocation is feasible and most profitable. A set of Pareto optimal solutions can be evaluated in order to determine the most optimal runway allocation distribution. The conclusion that can be drawn from this research is that flexible allocation can have significant impact on both fuel usage and emissions, while adhering to the current regulations. Depending on the flexibility of available runways, mainly restricted by separation- and noise regulations, runway demand, local conditions and maintenance, savings are possible. For scenarios where there is room for flexibility, savings are evident. For restricted scenarios, due to wind- or visibility conditions, potential savings exist, although to a lesser extend. The level of runway demand plays a role, as most flexibility and potential savings are obtainable during off-peaks. Annual savings can amount to significant fuel and emission reduction. The described runway allocation tool has the generic abilities of being scalable to wide variety of airports and their characteristics. Other airports, a larger set of aircraft and aircraft types, different arrival and departure operations can all be added to the model due to the generic characteristics. This aids further research and eventual application of flexible arrival and departure runway allocation in the aviation industry.