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H2020Doctoral network2018–2021

MINOA · Mixed-Integer Non-Linear Optimisation Applications

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2018-01-01 → 2021-12-31
EU contribution
€3,016,287
Participants
19
Scheme
MSCA-ITN-ETN

Lines connect the coordinator with its partners.

Results in brief

Mixed-Integer Non-Linear Optimisation Applications

Building upon the achievements of the Marie-Curie ITN Mixed-Integer Non-Linear Optimisation (MINO), the goal of MINOA was to train the next generation of highly qualified researchers and managers in applied mathematics, operations research and computer science that are able to face the modern challenges of European and international relevance in areas such as energy, logistics, engineering, natural sciences, and data analytics. Fourteen Early-Stage Researchers (ESRs) were trained through an innovative training programme based on individual research projects motivated by these applications that due to their high complexity will stimulate new developments in the field. The mathematical challenges can neither be met by using a single optimisation method alone nor isolated by single academic partners. As special challenges, the ESRs worked on dynamic aspects and optimisation in real time, optimisation under uncertainty, multilevel optimisation and noncommutativity in quantum computing. The ESRs devised new effective algorithms and computer implementations. They validated their methods for the applications with respect to metrics that they have defined. All ESRs derived recommendations, both for MINO applications and for the effectiveness of the novel methodologies. The ESRs belong to a new generation of highly-skilled researchers that strengthens Europe's human capital base in R&I in the fast growing field of mathematical optimisation. The ESR projects were pursued in joint supervision between experienced practitioners from leading European industries and optimisation experts, covering a wide range of scientific fields. This proved to be possible even in the pandemic.

Data: CORDIS, © European Union

Project objective

Building upon the achievements of the Marie-Curie ITN Mixed-Integer Non-Linear Optimization (MINO) (2012 - 2016), the goal of the Mixed-Integer Non-Linear Optimisation Applications (MINOA) proposal is to train the next generation of highly qualified researchers and managers in applied mathematics, operations research and computer science that are able to face the modern imperative challenges of European and international relevance in areas such as energy, logistics, engineering, natural sciences, and data analytics. Twelve Early-Stage Researchers (ESRs) will be trained through an innovative training programme based on individual research projects motivated by these applications that due to their high complexity will stimulate new developments in the field. The mathematical challenges can neither be met by using a single optimisation method alone, nor isolated by single academic partners. Instead, MINOA aims at building bridges between different mathematical methodologies and at creating novel and effective algorithmic enhancements. As special challenges, the ESRs will work on dynamic aspects and optimisation in real time, optimisation under uncertainty, multilevel optimization and non-commutativity in quantum computing. The ESRs will devise new effective algorithms and computer implementations. They will validate their methods for the applications with respect to metrics that they will define. All ESRs will derive recommendations, both for optimised MINO applications and for the effectiveness of the novel methodologies. These ESRs belong to a new generation of highly-skilled researchers that will strengthen Europe'e human capital base in R&I in the fast growing field of mathematical optimisation. The ESR projects will be pursued in joint supervision between experienced practitioners from leading European industries and leading optimisation experts, covering a wide range of scientific fields (from mathematics to quantum computing and real-world applications).

Original text from CORDIS.

Participants

  • FRIEDRICH-ALEXANDER-UNIVERSITAET ERLANGEN-NUERNBERG · ErlangenCoordinatorGermany
  • ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA · BolognaItaly
  • BAYERISCHE FORSCHUNGSALLIANZ BAVARIAN RESEARCH ALLIANCE GMBH · MUNCHENGermany
  • CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisFrance
  • COMPAGNIE IBM FRANCE SAS · Bois ColombesFrance
  • CONSIGLIO NAZIONALE DELLE RICERCHE · RomaItaly
  • CRAY COMPUTER GMBH · BaselSwitzerland
  • MANAGEMENT, ARTIFICIAL INTELLIGENCE AND OPERATIONS RESEARCH SOCIETA' A RESPONSABILITA' LIMITATA · LuccaItaly
  • OPTIT SRL · BOLOGNAItaly
  • ORTEC OPTIMIZATION TECHNOLOGY BV · ZoetermeerNetherlands
  • RUPRECHT-KARLS-UNIVERSITAET HEIDELBERG · HeidelbergGermany
  • SHELL GLOBAL SOLUTIONS INTERNATIONAL BV · 's-Gravenhage (Den Haag)Netherlands
  • SIEMENS AKTIENGESELLSCHAFT · MunchenGermany
  • STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN · UtrechtNetherlands
  • TECHNISCHE UNIVERSITAT DORTMUND · DortmundGermany
  • TILBURG UNIVERSITY- UNIVERSITEIT VAN TILBURG · TilburgNetherlands
  • UNIVERSITA DI PISA · PisaItaly
  • UNIVERSITAET KLAGENFURT · Klagenfurt am WörtherseeAustria
  • UNIVERSITAT ZU KOLN · KolnGermany

Links

Data: CORDIS, © European Union