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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1. Purpose of the ResearchThe research aims at developing a concept of operations (ConOps) that could connect aviation and all existing and future transport modes into an overall efficient transport network. Such ConOps should provide future passengers with a rapid and seamless travel experience.2. Research design, Methodology or ApproachThis paper describes a ConOps based on an ATM (Air Traffic Management) for a holistic traffic management system. For this purpose, the influences of quality management systems and other organizational facilities on the quality of passenger travel were examined. Various management systems like resources, traffic information, energy, fleet emergency calls, security and infrastructure, and applications such as weather information platforms and tracking systems have been integrated.3. Expected research findingsThe ConOps is intended to pave the way to cross-modal traffic management, in which the preferences of the travellers have a high priority. The first results show that the needs of the passengers can only be met in advance, and the traffic resources can only be used economically through close cooperation and coordination of these management systems and applications with regard to possible synergies and interactions.4. Summary of the originality/contributionTo develop these ConOps, general and traffic management systems next to basic principles of quality management were researched in the literature, which could be summarized in a Total Traffic Management System (TTM). The ATM experience served as a model example. The ConOps can be used as a basis to build a previously non-existing TTM that can be used to manage the future of travelling and future transport modes.
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Airport operations are undergoing significant change, having to meet pandemic requirements in addition to intrinsic security requirements. Although air traffic has declined massively, airports are still the critical hubs of the air transport network. The new restrictions due to the COVID-19 pandemic pose new challenges for airport operators in redesigning airport terminals and managing passenger flows. To evaluate the impact of COVID-19 restrictions, we implement a reference airport environment. In this Airport in the Lab environment we will demonstrate the operational consequences derived from the new operational requirements. In addition, countermeasures to mitigate any negative impacts of these changes are tested. The results highlight emerging issues that the airport will most likely face and possible solutions. Finally, we could apply the findings and lessons learned from our testing at our reference airport to a real airport.
The research, supported by our partners, sets out to understand the drivers and barriers to sustainable logistics in port operations using a case study of drone package delivery at Rotterdam Port. Beyond the technical challenges of drone technology as an upcoming technology, it needs to be clarified how drones can operate within a port ecosystem and how they could contribute to sustainable logistics. KRVE (boatmen association), supported by other stakeholders of Rotterdam port, approached our school to conduct exploratory research. Rotterdam Port is the busiest port in Europe in terms of container volume. Thirty thousand vessels enter the port yearly, all needing various services, including deliveries. Around 120 packages/day are delivered to ships/offices onshore using small boats, cars, or trucks. Deliveries can take hours, although the distance to the receiver is close via the air. Around 80% of the packages are up to 20kg, with a maximum of 50kg. Typical content includes documents, spare parts, and samples for chemical analysis. Delivery of packages using drones has advantages compared with traditional transport methods: 1. It can save time, which is critical to port operators and ship owners trying to reduce mooring costs. 2. It can increase logistic efficiency by streamlining operations. 3. It can reduce carbon emissions by limiting the use of diesel engines, boats, cars, and trucks. 4. It can reduce potential accidents involving people in dangerous environments. The research will highlight whether drones can create value (economic, environmental, social) for logistics in port operations. The research output links to key national logistic agenda topics such as a circular economy with the development of innovative logistic ecosystems, energy transition with the reduction of carbon emissions, societal earning potential where new technology can stimulate the economy, digitalization, key enabling technology for lean operations, and opportunities for innovative business models.
