Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case.
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Paris Charles de Gaulle Airport was the second European airport in terms of traffic in 2019, having transported 76.2 million passengers. Its large infrastructures include four runways, a large taxiway network, and 298 aircraft parking stands (131 contact) among three terminals. With the current pandemic in place, the European air traffic network has declined by −65% flights when compared with 2019 traffic (pre-COVID-19), having a severe negative impact on the aviation industry. More and more often taxiways and runways are used as parking spaces for aircraft as consequence of the drastic decrease in air traffic. Furthermore, due to safety reasons, passenger terminals at many airports have been partially closed. In this work we want to study the effect of the reduction in the physical facilities at airports on airspace and airport capacity, especially in the Terminal Manoeuvring Area (TMA) airspace, and in the airport ground side. We have developed a methodology that considers rare events such as the current pandemic, and evaluates reduced access to airport facilities, considers air traffic management restrictions and evaluates the capacity of airport ground side and airspace. We built scenarios based on real public information on the current use of the airport facilities of Paris Charles de Gaulle Airport and conducted different experiments based on current and hypothetical traffic recovery scenarios. An already known optimization metaheuristic was implemented for optimizing the traffic with the aim of avoiding airspace conflicts and avoiding capacity overloads on the ground side. The results show that the main bottleneck of the system is the terminal capacity, as it starts to become congested even at low traffic (35% of 2019 traffic). When the traffic starts to increase, a ground delay strategy is effective for mitigating airspace conflicts; however, it reveals the need for additional runways
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This paper presents an innovative approach that combines optimization and simulation techniques for solving scheduling problems under uncertainty. We introduce an Opt–Sim closed-loop feedback framework (Opt–Sim) based on a sliding-window method, where a simulation model is used for evaluating the optimized solution with inherent uncertainties for scheduling activities. The specific problem tackled in this paper, refers to the airport capacity management under uncertainty, and the Opt–Sim framework is applied to a real case study (Paris Charles de Gaulle Airport, France). Different implementations of the Opt–Sim framework were tested based on: parameters for driving the Opt–Sim algorithmic framework and parameters for riving the optimization search algorithm. Results show that, by applying the Opt–Sim framework, potential aircraft conflicts could be reduced up to 57% over the non-optimized scenario. The proposed optimization framework is general enough so that different optimization resolution methods and simulation paradigms can be implemented for solving scheduling problems in several other fields.
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The capacity of the newly inaugurated airport terminal in Mexico City, opened in 2022, has sparked debates regarding its adequacy to accommodate future demand. To address this critical question, our study employs simulation-based analysis to assess the terminal's true potential. By simulating various scenarios, we aim to provide insights into its capacity to handle increasing passenger loads over the coming years and decades. Furthermore, our analysis identifies potential challenges and issues that may arise with the terminal's growth. This research seeks to offer valuable perspectives for stakeholders involved in the airport's planning and management, contributing to informed decisionmaking in ensuring efficient and sustainable aviation infrastructure.
MULTIFILE
Airport management is regularly challenged by the task of assigning flights to existing parking positions in the most efficient way while complying with existing policies, restrictions and capacity limitations. However, such process is frequently disrupted by various events, affecting punctuality of airline operations. This paper describes an innovative approach for obtaining an efficient stand assignment considering the stochastic nature of airport environment. Furthermore, the presented methodology combines benefits of Bayesian modelling and metaheuristics for generating solutions that are more robust to airport flight schedule perturbations. In addition, this paper illustrates that the application of the presented methodology combined with simulation provides a valuable tool for assessing the robustness of the developed stand assignment to flight delays.
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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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Airports and surrounding airspaces are limited in terms of capacity and represent the major bottleneck in the air traffic management system. This paper proposes a two level model to tackle the integrated optimization problem of arrival, departure, and surface operations. The macroscopic level considers the terminal airspace management for arrivals and departures and airport capacity management, while the microscopic level optimizes surface operations and departure runway scheduling. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on real-world case studies of Paris Charles De-Gaulle airport, show the benefits of this integrated approach.
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Predictive models and decision support toolsallow information sharing, common situational awarenessand real-time collaborative decision-making betweenairports and ground transport stakeholders. To supportthis general goal, IMHOTEP has developed a set of modelsable to anticipate the evolution of an airport’s passengerflows within the day of operations. This is to assess theoperational impact of different management measures onthe airport processes and the ground transport system. Twomodels covering the passenger flows inside the terminal andof passengers accessing and egressing the airport have beenintegrated to provide a holistic view of the passengerjourney from door-to-gate and vice versa.This paper describes IMHOTEP’s application at two casestudy airports, Palma de Mallorca (PMI) and London City(LCY), at Proof of Concept (PoC-level) assessing impactand service improvements for passengers, airport operatorsand other key stakeholders.For the first time onemeasurable process is created to open up opportunities forbetter communication across all associated stakeholders.Ultimately the successful implementation will lead to areduction of the carbon footprint of the passenger journeyby better use of existing facilities and surface transportservices, and the delay or omission of additional airportfacility capacities.
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In Nederland gebruiken 65 plussers drie keer zoveel medicijnen als de gemiddelde Nederlander. Voor 75 plussers geldt dat zij vijf keer zoveel medicijnen gebruiken. In combinatie met leeftijdsgerelateerde natuurlijke veranderingen in het metabolisme, verminderde cognitie, multi-morbiditeit, verminderde nierfunctie, polyfarmacie en verminderde capaciteit tot herstel, zijn ouderen kwetsbaar voor medicatiegerelateerde problemen. Thuiszorg cliënten zijn doorgaans ouder dan 65 jaar, waardoor er vaker sprake is van polyfarmacie en verminderde cognitie. Daarom bevinden zich vooral in deze populatie cliënten, die kwetsbaar zijn voor medicatiegerelateerde problemen. Verschillende studies hebben aangetoond dat huisartsen en apothekers een bijdrage kunnen leveren aan het herkennen van medicatiegerelateerde problemen bij hun patiënten. Er is echter weinig aandacht besteed aan het vroegsignaleren van observaties die kunnen duiden op een medicatie gerelateerd probleem door thuiszorgmedewerkers. In aanvulling op de huisarts en apotheker zouden thuiszorgmedewerkers, die hun patiënten op regelmatige basis thuis bezoeken, een bijdrage kunnen leveren aan het vroegsignaleren van potentiële medicatiegerelateerde problemen. Het doel van dit proefschrift is het: 1. verkennen van de opvattingen van ouderen ten aanzien van hun medicatie en hun medicatie management capaciteit gerelateerd aan zelfmanagement vaardigheden en cognitie; 2. beschrijven van de kennis, houding en medicatie management praktijk van thuiszorgmedewerkers; 3. vaststellen of een gestandaardiseerde observatielijst leidt tot vroegsignalering van potentiële medicatiegerelateerde problemen in de thuiszorg
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