Multi-agent system for an airline operations control centre

Estágio realizado na TAP Portugal e orientado pelo Eng.º António CastroTese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Impact of the organizational structure on operations management : the airline operations control centre case study

Documento confidencial. Não pode ser disponibilizado para consultaTese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Complexity challenges in ATM

After more than 4 years of activity, the ComplexWorld Network, together with the projects and PhDs covered under the SESAR long-term research umbrella, have developed sound research material contributing to progress beyond the state of the art in fields such as resilience, uncertainty, multi-agent systems, metrics and data science. The achievements made by the ComplexWorld stakeholders have also led to the identification of new challenges that need to be addressed in the future. In order to pave the way for complexity science research in Air Traffic Management (ATM) in the coming years, ComplexWorld requested external assessments on how the challenges have been covered and where there are existing gaps. For that purpose, ComplexWorld, with the support of EUROCONTROL, established an expert panel to review selected documentation developed by the network and provide their assessment on their topic of expertise

Evolutionary Computation methods applied to Operational Control Centers

Durante a execução de um plano operacional, existe a possibilidade do mesmo sofrer rupturas causadas por eventos não esperados. As rupturas afetam pelo menos três dimensðes sobre as quais as companhias aéreas e os centros de controlo operacional devem ter em conta, nomeadamente os passageiros, a tripulação e os aviðes. Normalmente, um ruptura é um estado durante o qual uma operação que esteja a ser executada é afetada por um desvio (que é grande o suficiente para causar uma mudança) do plano original e, por vezes, levando a que o plano não seja execuível. Exem- plos de eventos que podem causar rupturas são condiçðes meteorológicas, ameaças ou ataques terroristas e avarias nos aviðes.Disruption Management, pode então ser definido como o processo que começa após detectar o desvio do plano original. Depois da ruptura, o plano é mudado e nunca mais vai estar tão perto da solução ótima quanto estava antes da ruptura, sendo que pode mesmo vir a ser impossível a continuação do plano. De qualquer maneira existe a necessidade de rever o plano e de minimizar o impacto causado pela ruptura.O MASDIMA é uma grande ajuda para os Centros de Controlo Operacionais das companhias aéreas encontrarem soluçðes para rupturas durante a execução de um plano operacional, e para melhorar quer o tempo de computação quer a qualidade das soluçðes, existe a necessidade de melhorar o sistema. Isto traduz-se em minimizar o impacto quer a ao nvel dos custos quer ao nvel dos atrasos.Para lidar com este problema serão implementados três agentes, sendo que cada um representa um algoritmo evolutivo diferente (Particle Swarm Optimisation, Ant Colony Optimisation e Ge- netic Algorithms) e estarão relacionados com a dimensão avião relativa ao problema. Estes três agentes serão implementados num Sistema Multi-Agente chamado de MASDIMA que represen- tará o Centro de Controlo Operacional.During the execution of an operational plan, there is the likelihood of this plan being affected by some disruptions caused by unexpected events. The disruptions affect at least three dimensions that airline companies and the operational control centers must take into account which are pas- senger, crew and aircraft. Usually, a disruption is a state during which the current operation being executed is affected by a deviation (which is large enough to cause a change) from the original plan, and sometimes unfortunately it leads to an unfeasible plan. Examples of events that might cause disruptions are bad weather, threats or terrorist attacks and aircraft malfunctions.Disruption Management, can be defined as the process that starts after the deviation from the original plan is detected. After the disruption, the plan is changed and it will no longer be as close as it was from an optimal plan or it can even turn into an unfeasible plan. Either way there is a need to review the plan and try to minimize the impact caused by the disruption.MASDIMA is useful to help Airline Operation Control Centers finding a solution to disrup- tions during an operational plan, and in order to improve both computing time and the quality of solutions, there is a need to improve the system. This will translate in minimising the impact both in terms of costs or delays.To deal with that problem three agents will be implemented that will reflect, each one, different evolutionary computation algorithms (Particle Swarm Optimisation, Ant Colony Optimisation and Genetic Algorithms) and are related to the aircraft dimension of the problem. These agents will be implemented on a Multi-Agent System named MASDIMA that represents an Operation Control Center

Digital Disruption Solution

Since March, 2017, the cost of denied boarding began to draw the attention of all Brazilian airlines because of the Resolution 400 of the Brazilian National Civil Aviation Agency. This Resolution covers several items but here we will focus on the penalty that the airlines need to pay for each passenger who had his boarding denied involuntarily in domestic flights. An operating restriction of an airline may result in the denial of boarding of a specified number of passengers. When this process of selecting the passengers and their accommodation on another flight happens very close to the time of departure, the probability of delays is high. We believe that is possible to reduce the contingency costs based on identifying volunteer passengers in advance. Since the operational restriction, whether caused by excess weight or seat limitations, is not always predicted in advance, we are considering having the passenger profile of all flights in advance to understand their needs and looking to identify the more flexible ones. Our goal is to create a plug-in that any airline could use in their self-service check in channels, and making direct communication with the passenger. It also could become a way to offer proactive accommodation options as well as commercial compensations due to itinerary or ticket schedule change

Recent developments and future trends of industrial agents

The agent technology provides a new way to design and engineer control solutions based on the decentralization of control over distributed structures, addressing the current requirements for modern control systems in industrial domains. This paper presents the current situation of the development and deployment of agent technology, discussing the initiatives and the current trends faced for a wider dissemination and industrial adoption, based on the work that is being carried out by the IEEE IES Technical Committee on Industrial Agents

Emerging Technology IS Course Design: Blockchain for Business Example

IS curricula require constant updating to accommodate the emergence of new technologies. Designing and delivering effective emerging technology courses within the constraints of existing programs remains an important challenge faculty face. This paper presents a template for approaching these courses from a learning theory perspective. Results of tests of this template, developed for teaching blockchain, indicate that it successfully strikes the balance needed in an IS program while simplifying the work of designing the structure of an emerging technology course. Additionally, this design was able to deliver this success in an online format, which can be a more challenging format for observing application of knowledge. Blockchain is a disruptive emerging technology opportunity for businesses to unlock value through trusted and “smart” peer-to-peer transactions, wherein smart means businesspeople can custom design processes for verification and transfer of assets. The blockchain example provided here includes a flexible 7-scenario design targeted to enable a constructive, project-based learning approach focused on authentic learning experiences. The template as applied to blockchain may be used directly or adapted for easier development of other emerging technology courses

From physical marketing to web marketing

Reviews the criticism of the 4P marketing mix framework as the basis of traditional and virtual marketing planning. Argues that the customary marketing management approach, based on the popular marketing mix 4Ps paradigm, is inadequate in the case of virtual marketing. Identifies two main limitations of the marketing mix when applied in online environments namely the role of the Ps in a virtual commercial setting and the lack of any strategic elements in the model. Identifies the critical factors of the Web marketing and argues that the basis for successful e-commerce is the full integration of virtual activities into the company's physical strategy, marketing plan and organisational processes. The 4S elements of the Web marketing mix framework offer the basis for developing and commercialising business to consumer online projects. The model was originally developed for educational purposes and has been tested and refined by means of three case studies

Engage D1.2 Final Project Results Report

This deliverable summarises the activities and results of Engage, the SESAR 2020 Knowledge Transfer Network (KTN). The KTN initiated and supported multiple activities for SESAR and the European air traffic management (ATM) community, including PhDs, focused catalyst fund projects, thematic workshops, summer schools and the launch of a wiki as the one-stop, go-to source for ATM research and knowledge in Europe. Key throughout was the integration of exploratory and industrial research, thus expediting the innovation pipeline and bringing researchers together. These activities laid valuable foundations for the SESAR Digital Academy