Projects since 2019

Coordination: Multiobjective Network Interdiction (2020-2021), MOCO-SEARCH (2018-2020)

Participation: SusTrainable (2020-2024), ImAppNIO (2018-2020), MobiWise (2017-2020)

Fellowships

Research projects

Multiobjective Network Interdiction

Multiobjective Network Interdiction is a German-Portuguese bilateral project, running from 2/2020 to 12/2021, funded by FCT and DAAD, and with partners from University of Coimbra, University of Lisbon, University of Wuppertal and Technical University of Kaiserlautern.

Summary: Network interdiction problems usually involve two players, often called the attacker and the defender. In general, while the defender aims at optimizing the performance of a given network, the attacker attempts to optimally deteriorate network performance by altering the network subject to the cost of such alterations remaining within a given interdiction budget. These problems arise in various application areas such as cyber security, infectious disease control, drug interdiction, and antiterrorism, among others. However, real-world applications are often such that one has to consider various conflicting objectives to obtain a set of non-inferior solutions, called the Pareto-optimal solutions. Whereas single- objective network interdiction problems have received lots of attention in the literature, the literature on multiobjective network interdiction problems is rather limited. This project aims at advancing the study of network interdiction from a multiobjective perspective.

ALGO Lab participants:

MOCO-SEARCH - Bridging the gap between exact methods and heuristics for multi-objective search is a French-Portuguese bilateral project, running from 1/2018 to 12/2020, funded by FCT and CNRS, and with partners from University of Coimbra, University of Lisbon, Université de Lille and Université Littoral Côte d’Opale.

Summary: Many real-life applications can be modeled as combinatorial optimization problems with several objectives. Depending of the time available, these problems can be solved by exact or heuristic approaches. Despite the advances on these two solution methods, there is currently little understanding on what they have in common and how they can be combined to solve these problems in a more effective manner. The MOCO-Search project aims to fill this gap. The goal is to establish the link between the design principles of exact and heuristic methods, to identify features that make a problem more difficult to be solved by each method, and to improve their performance by hybridizing search strategies. Special emphasis is given to rigorous performance assessment, benchmarking, and general-purpose guidelines for the design of exact and heuristic multi-objective search.

ALGO Lab participants:

URL: https://sites.google.com/view/moco-search

SusTrainable

SusTrainable is a Eramus+ project, running from 11/2020 to 10/2024, with partners from University of Plovdiv “Paisii Hilendarski”, University Juraj Dobrila of Pula, University of Rijeka, Eötvös Loránd University, University of Minho, University of Coimbra (Coordinating Institution), Babes-Bolyai University of Cluj-Napoca, Technical University of Košice, University of Amsterdam, and Radboud University Nijmegen.

Summary: Our objective is to train the future avant-garde software engineers for the sustainable software and ICT that the knowledge-based, environmentally concerned societies of the 21st century demand. The majority of summer school participants are close to their transition from learning to doing and will soon join the European software engineering workforce. They will carry the ideas, concepts and methods they learned at the summer schools into industrial software engineering practice worldwideacross Europe. Furthermore, they will act as facilitators and multipliers alike for a sustainable future software-driven Europe. Conversely, we provide the ubiquitous enthusiasm of the younger generation for sustainable development a constructive, meaningful and high-impact route forward.

ALGO Lab participants:

URL: https://sustrainable.github.io

MobiWise

MobiWise is a national research project, running from 1/2017 to 12/2020, funded by FEDER and FCT, and with partners from Telecommunications Institute, University of Coimbra and University of Aveiro.

Summary: MobiWise aims to enhance mobility in the cities, both for commuters and for tourists, through the development of a 5G platform that encompasses an access infrastructure filled with sensors, people and vehicles. The project will connect any sensor, person and vehicle, and will use all possible information to improve the user mobility, through a complete network and services platform for an Internet of Things real deployment in a smart city.

ALGO Lab participants:

URL: http://mobiwise.av.it.pt/

ImAppNIO

ImAppNIO – Improving Applicability of Nature-inspired Optimisation by Joining Theory and Pratice is a COST Action (CA15140), running from 1/2018 to 12/2020, funded by EC, and with partners from 30 countries.

Summary: Nature-inspired search and optimisation heuristics are easy to implement and apply to new problems. However, in order to achieve good performance it is usually necessary to adjust them to the problem at hand. Theoretical foundations for the understanding of such approaches have been built very successfully in the past 20 years but there is a huge disconnect between the theoretical basis and practical applications. The development of powerful analytical tools, significant insights in general limitations of different types of nature-inspired optimisation methods and the development of more practically relevant perspectives for theoretical analysis have brought impressive advances to the theory-side of the field. However, so far impact on the application-side has been limited and few people in the diverse potential application areas have benefitted from these advances.

The main objective of the COST Action is to bridge this gap and improve the applicability of all kinds of nature-inspired optimisation methods. It aims at making theoretical insights more accessible and practical by creating a platform where theoreticians and practitioners can meet and exchange insights, ideas and needs; by developing robust guidelines and practical support for application development based on theoretical insights; by developing theoretical frameworks driven by actual needs arising from practical applications; by training Early Career Investigators in a theory of nature-inspired optimisation methods that clearly aims at practical applications; by broadening participation in the ongoing research of how to develop and apply robust nature-inspired optimisation methods in different application areas.

ALGO Lab participants:

URL: https://imappnio.dcs.aber.ac.uk

Fellowships

PhD fellowships

Research grants

Starting research grants