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EU funding (€3,016,287): Mixed-Integer Non-Linear Optimisation Applications Hor 28 Aug 2017 EU Research and Innovation programme "Horizon"
Overview
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Mixed-Integer Non-Linear Optimisation Applications
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).
Funded Companies:
| Company name | Funding amount |
| Bayerische Forschungsallianz Bavarian Research Alliance GmbH | ? |
| Alma Mater Studiorum - Universita Di Bologna | €458,776 |
| Centre National de la Recherche Scientifique CNRS | €262,876 |
| Compagnie IBM France SAS | €0.00 |
| Consiglio Nazionale Delle Ricerche | €258,061 |
| Friedrich-Alexander-Universitaet Erlangen-Nuernberg | €235,371 |
| Management, Artificial Intelligence AND Operations Research Societa' A Responsabilita' Limitata | €258,061 |
| Ruprecht-Karls-Universitaet Heidelberg | €249,216 |
| Stichting Nederlandse Wetenschappelijk Onderzoek Instituten | €255,374 |
| Technische Universitat Dortmund | €235,371 |
| Tilburg University- Universiteit Van Tilburg | €255,374 |
| Universitaet Klagenfurt | €298,590 |
| Universitat ZU Koln | €249,216 |
Source: https://cordis.europa.eu/project/id/764759
The filing refers to a past date, and does not necessarily reflect the current state. The latest known state is available on the following page: Bayerische Forschungsallianz (Bavarian Research Alliance) GmbH, Munich, Germany.
