Dit eindrapport behandelt het onderzoek van CDM@Airports, gericht op Collaborative Decision Making in de logistieke processen van luchtvrachtafhandeling op Nederlandse luchthavens. Dit project, met een looptijd van ruim twee jaar, is gestart op 8 november 2021 en geëindigd op 31 december 2023. HET PROJECT CDM@AIRPORTS OMVAT DRIE WERKPAKKETTEN: 1. Projectmanagement, dit betreft de algehele aansturing van het project incl. stuurgroep, werkgroep en stakeholdermanagement. 2. Onderzoeksactiviteiten, bestaande uit a) cross-chain-samenwerking, b) duurzaamheid en c) adoptie van digitale oplossingen voor datagedreven logistiek. 3. Management van een living lab, een ‘quadruple-helix-setting’ die fysieke en digitale leeromgevingen integreert voor onderwijs en multidisciplinair toegepast onderzoek.
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With the increase of needs for controlling the passengers that use different modes of transport such as airports, ports, trains, or future ones as hyper loops, security facilities are a key element to be optimized. In the current study, we present an analysis of a security area within an airport with particular restrictions. To improve the capacity, different categories and policies were devised for processing passengers and we propose to adapt the system to these categories and policies. The results indicated that, by designing a proper category in combination with novel technology, it is possible to increase the capacity to values of 2 digits (in terms of passengers/day). As a proof-of-concept, we use a case study of an area within an airport in Mexico based on data and layout of early 2019.
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Airport infrastructure evolves alongside legacy systems and processes that limits the ability to fully realise the efficiency potential of costly renovations. Airports will continue to take advantage of current and future technologies. Nevertheless, for such systems to work as efficiently as possible, the passenger should play an active role. This paper analyzes the effect of a new type of emerging ’smart passenger’, one that cooperates to be enabled to use the most efficient processes for a seamless experience. The technological and behavioural enhancements areassessed with the simulation of two case studies: London City and Palma de Mallorca airports. Results indicate that the introduction of this type of passenger brings benefit in terms of level of service indicators not only to this type of passenger but also to the traditional ones (business, visitor and leisure). However,the impact differs depending on the type of airport and the proportion of ’smart passengers’.
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The constant growth of air traffic, especially in Europe, is putting pressure on airports, which, in turn, are suffering congestion problems. The airspace surrounding airport, terminal manoeuvring area (TMA), is particularly congested, since it accommodates all the converging traffic to and from airports. Besides airspace, airport ground capacity is also facing congestion problems, as the inefficiencies coming from airspace operations are transferred to airport ground and vice versa. The main consequences of congestion at airport airspace and ground, is given by the amount of delay generated, which is, in turn, transferred to other airports within the network. Congestion problems affect also the workload of air traffic controllers that need to handle this big amount of traffic.This thesis deals with the optimization of the integrated airport operations, considering the airport from a holistic point of view, by including operations such as airspace and ground together. Unlike other studies in this field of research, this thesis contributes by supporting the decisions of air traffic controllers regarding aircraft sequencing and by mitigating congestion on the airport ground area. The airport ground operations and airspace operations can be tackled with two different levels of abstractions, macroscopic or microscopic, based on the time-frame for decision-making purposes. In this thesis, the airport operations are modeled at a macroscopic level.The problem is formulated as an optimization model by identifying an objective function that considers the amount of conflicts in the airspace and capacity overload on the airport ground; constraints given by regulations on separation minima between consecutive aircraft in the airspace and on the runway; decision variables related to aircraft entry time and entry speed in the airspace, landing runway and departing runway choice and pushback time. The optimization model is solved by implementing a sliding window approach and an adapted version of the metaheuristic simulated annealing. Uncertainty is included in the operations by developing a simulation model and by including stochastic variables that represent the most significant sources of uncertainty when considering operations at a macroscopic level, such as deviation from the entry time in the airspace, deviation in the average taxi time and deviation in the pushback time. In this thesis, optimization and simulation techniques are combined together by developing two methods that aim at improving the solution robustness and feasibility. The first method acts as a validation tool for the optimized solution, and it improves the robustness of solution by iteratively fine-tuning some of the optimization model input parameters. The second method embeds the optimization in a simulation environment by taking full advantage of the sliding window approach and creating a loop for a continuous improvement of the optimized solution at each window of the sliding window approach. Both methods prove to be effective by improving the performance, lowering the total amount of conflicts up to 23.33% for the first method and up to 11.2% for the second method, however, in contrast to the deterministic method, the two methods they are not able to achieve a conflict-free scenario due to the effect of uncertainty.In general, the research conducted in this thesis highlights that uncertainty is a factor that affects to a large extent the feasibility of optimized solution when applied to real-world instances, and it, moreover, confirms that using simulation together with optimization has the potentiality toivdeal with uncertainty. The framework developed can be potentially applied to similar problems and different optimization solving methods can be adapted to it.Keywords: Optimization, Simulation, Integrated airport operations, Uncertainty
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This study presents a model-based analysis of the groundconnectivity performance of the future Santa Lucia-Mexico City multi-airport system. The plan of the currentgovernment is to connect the two airports by a dedicatedline, either by bus or other transport so that passengersand airlines can get the benefit of a coordinatedoperation. Performance indicators such as minimumconnecting time, vehicle utilization and passengerwaiting time are used to evaluate the future performance.Results reveal that when all passengers are allowed to usethe connection, a big number of vehicles are required forproviding a good level of service while in the case of arestricted use to only transfer passengers the operationwith Bus would have a good performance.
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The aeronautical traffic capacity is approaching its limits. This is especially true for airports where airports are constrained to resources such as runways. Consequences of full capacity traffic can be translated to delays and safety issues such as higher collisions risks. One important part of traffic are points where traffic is routed, such as transfer of flights to different ANSPs, sector changes, and merging to meter fixes for landing. There are cases where some entry points to sections are close to maximum capacity, while other entry points to the same section have more capacity. Within the framework of FF-ICE, this paper presents the operational idea of Tactical Demand Tailoring, which consists of balancing traffic by re-routing traffic hours before the arrival of aircraft to a given congested section. This paper proposes the conditions that must be met for TDT to be operationally feasible, and it discusses the potential benefits to increase capacity at overloaded parts of the airspace. Results showed that flights exist under the current flight conditions that can be re-routed to increase capacity. On average, these re-routes result in an approximate 1.9% increase in flight track length. Furthermore, a real-world case study conducted at the Terminal Manoeuvring Area of Schiphol Airport demonstrates that the implementation of Tactical Demand Tailoring effectively mitigates delays.
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The current study presents a methodology for analysing and identifying the limitations in capacity of an airport, the methodology has been implemented in the case of Mexico City Airport which is a congested airport in Mexico. The methodology allows identifying what room is left for absorbing more traffic and what options are available while a new infrastructure is in place. The methodology revealed, that there is still room for absorbing more traffic under certain conditions and starting from that, actions can be taken in order to increase the capacity or reducing congestion in the airport.
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This study examines the effect of seat assignment strategies on the transfer time of connecting passengers at a hub airport. Passenger seat allocation significantly influences disembarkation times, which can increase the risk of missed connections, particularly in tight transfer situations. We propose a novel seat assignment strategy that allocates seats to nonpaying passengers after check-in, prioritising those with tight connections. This approach diverges from traditional methods focused on airline turnaround efficiency, instead optimizing for passenger transfer times and reducing missed connections. Our simulation, based on real-world data from Paris-Charles de Gaulle airport, demonstrates that this passenger-centric model decreases missed connections by 12%, enhances service levels, reduces airline compensation costs, and improves airport operations. The model accounts for variables such as seat occupancy,luggage, and passenger type (e.g., business, leisure) and is tested under various scenarios, including air traffic delays.
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