APRÈN. Portal de la producció docent del professorat de la UPC

Actualmente, existe un gran crecimiento a nivel mundial del tráfico aéreo. Debido a un aumento en la demanda y a ciertas limitaciones en los sistema actuales, se pueden producir situaciones de sobrecarga o overload, las cuales pueden llegar a comprometer la seguridad y la efeciencia operativa. El Sector Opening Scheme consiste en la sucesión de configuraciones de sectores que se van abriendo durante el dia. Hoy en día, este opening scheme suele carecer de flexibilidad para poder adaptarse a estos cambios en la demanda. En este trabajo de final de grado se pretende desarrollar un algoritmo de optimización en A* para mejorar el Sector Opening Scheme, analizando la demanda creciente actual y las capacidades de los diferentes sectores durante intervalos temporales. Como objetivo principal se ha fijado encontrar una serie de configuraciones más flexibles y eficientes para la apertura y el cierre de los sectores, tratando de optimizar de esta forma la distribución de los recursos y disminuyendo los escenarios de sobrecarga. Se han obtenido unos resultados en base a diferentes simulaciones, creadas con datos reales del espáceo aéreo, las cuales han demostrado una mejoría bastante significativa en la eficiencia operativa, reduciendo la sobrecarga en algunos casos en más de un 90% y disminuyendo los costes hasta un 20%. Finalmente, se ha podido concluir que esta gestión del espacio aéreo a través de una optimización del Sector Opening Scheme, no únicamente mejora la eficiencia y la seguridad, sino que además aporta una reducción sustancial en los costes operativos, indicando ser una solución factible para la gran creciente demanda del tráfico aéreo.

The constant increase in the complexity of the ATM environment is generating big challenges to the sector. One of the biggest challenges is balancing traffic demand (constantly growing) with the available capacity (at its limits). Traditional Demand-Capacity Balancing methods treat demand and capacity as separate entities, what outcomes not optimal. This project works on the implementation of an Holistic DCB model that is designed to integrate both demand and capacity management in a single framework. This will be performed by defining a model that analyses demand and capacity at the same time, which will provide a more accurate approach of the real operational conditions. The basis of the model is minimizing the operation cost of the hole studied time period. This cost is based on both the demand-related cost and the capacity-related cost. The optimization problem aims at finding the best sector opening scheme in the capacity side, by applying a big penalty to the measured overload, at the same time that it tries to find alternatives for the trajectories (either alternative trajectories and/or delay-appliance). With this, the model intends to \textbf{eliminate overload} (or keep it at the minimum feasible), maintaining demand below capacity in a more efficient and optimal way. The proposed model is addressed with an heuristic method (implemented in C++) based on Simulated Annealing and A-star (A*). This method allows to tackle large-scale scenarios, where finding an analytical solution is typcally not feasible for computation burden constraints. The method explores different airspace configurations, alternative trajectories and delay allocation, finding the optimal balance between minimizing delays and reducing operational costs. The results of the model's coded execution, which has been tested under various scenarios, show the validity of this method and its possible use to significantly reduce delays and operational costs while improving the overall efficiency of the system, while it leaves the door open to constant developments and improvements.

On this document, it has been evaluated the impact due to Covid 19 pandemic on the design and development process for the schedule of flights for an airline. This project also proposes the design and implementation of a tool that allows to analyze the impact and the viability of tactical cancellations. The tool provides information to evaluate whhich reaccommodation strategy for the disrupted passengers is the best and obtain the economic impact and the effect of the movement of passengers on the inventory. The principal consequence that all airlines have suffered has been the variability of the demand, which has been highly responsive to the changes of the mobility of the population and the specific sanitary evolution of each region around the world. To adapt to the demand, which has been mainly decreased, many airlines have faced to the need of reducing the published capacity that will finally be operated in order to minimize the loss. This implies the cancellation of bookings for millions of passengers that have been affected whom the regulation CE261 requires to find an alternative flight with the minor impact for the customer. To compute the impact of the cancellations and the reacommodations of each passenger, a support tool has been designed. This allows to simulate the adjustments that are produced on the inventory once the flight is cancelled, considering the type of booking and the requirements that must be considered according to the regulation and each typology of passenger. The implementation of the tool has provided to reduce more than 90% of the time resources required to realize this exercise manually. From the evaluation of the first results, it has been deduced that mostly for any scenario where the load factors are low, the impact and the cost does not have a dependency on the strategy and priority that has been selected. For other scenarios where the load factors are higher, there has been spotted some differences on the reacommodations and the cost for each one. However, those results cannot be considered defining due to the randomness of part of the input information used on the exercise which has been considered mainly with academic purposes. From this point, it is proposed to continue with the analysis of new scenarios, including the real and updated information in order to try to obtain more clear conclusions or detect patterns that may be helpful knowledge for subsequent capacity adjustments.

The main objective of this Bachelor Final Project is to design and implement a computation program in order to read the data of different flights (airplanes trajectories) and the configuration of the airspace (open sectors, geometry, etc.) in order to calculate the number of flights that crosses a sector. This will show which ones have the most aircraft entry rate. To achieve this goal, firstly the organization of the airspace will be explained as well as the functionality of all of its structures and their relationship with the flight phases. Secondly, the formats of all the data files used in this project will be mentioned as well as all of their characteristics and the information type they contain. In addition, the structure of the programs made will be explained as well as their functionality and the assumptions that had been taken into account. In order to validate them, the EUROCONTROL program NEST will be used. Finally, the program will be used in order to perform an analysis in the France airspace on a certain date and time. This will allow to observe its busiest sectors. As it will be proved, the sector with more traffic entering is the one that surrounds Paris. All this calculations will be made for two different types of file formats, one that represents the final flight plans sent by the airlines and the other that shows the paths done the day of the flight by the aircraft. With all that, the effect of the regulations made in the Europe flights will be shown. The final results are a small decrease in the number of planes crossing the busiest sectors in comparison with the number of planes crossing the not congested ones.