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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Section: Partnerships and Cooperations

European Initiatives

FP7 & H2020 Projects

  • Program: H2020

  • Project acronym: SYNERGY

  • Project title: Synergy for Smart Multi-Objective Optimisation

  • Duration: 02 2016 - 01 2019

  • Coordinator: Jožef Stefan Institute (JSI), Ljubljana, Slovenia

  • Other partners: University of Lille (France), Cologne University of Applied Sciences (Germany)

  • Abstract: Many real-world application areas, such as advanced manufacturing, involve optimization of several, often time-consuming and conflicting objectives. For example, they require the maximization of the product quality while minimizing the production cost, and rely on demanding numerical simulations in order to assess the objectives. These, so-called multi-objective optimization problems can be solved more efficiently if parallelization is used to execute the simulations simultaneously and if the simulations are partly replaced by accurate surrogate models.

Collaborations in European Programs, Except FP7 & H2020

  • Program: COST CA15140

  • Project acronym: ImAppNIO

  • Project title: Improving applicability of nature-inspired optimization by joining theory and practice

  • Duration: 2016-2019

  • Coordinator: Thomas Jansen

  • Abstract: 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.

Collaborations with Major European Organizations

  • MARO: University of Mons (BELGIUM), Parallel surrogate-assisted optimization, large-scale exact optimization

  • University of Ceara (BRAZIL), Large-scale GPU-accelerated tree-based optimization

  • University of Luxembourg (LUXEMBOURG), Energy-aware scheduling in Cloud computing systems

  • University of Oviedo (SPAIN), Optimization under uncertainty for fuzzy flow shop scheduling

  • University of Coimbra and University of Lisbon (PORTUGAL), Exact and heuristic multi-objective search

  • University of Manchester (UNITED KINGDOM), Local optimality in multi-objective optimization

  • University of Elche and University of Murcia (SPAIN), Matheuristics for DEA