Number of documents

1

Michael Poss


CNRS researcher at LIRMM, team MAORE

Short CV

I graduated in Mathematics from the Université Libre de Bruxelles, and in Operational Research from the University of Edinburgh. My thesis was done at the GOM research group from the Université Libre de Bruxelles, under the supervision of Bernard Fortz, Martine Labbé, and François Louveaux. During my PhD, I spent time in Rio de Janeiro, working at the Universidade Federal do Rio de Janeiro and at the CEPEL, working with Claudia Sagastizabal and Luciano Moulin. After my thesis was defended in Feburary 2011, I spent a couple of months at the Universidade de Aveiro, followed by a postdoctoral stay at the CMUC from the Universidade de Coimbra. I was a CNRS researcher at Heudiasyc from October 2012 to January 2015 and joined the LIRMM in February 2015. I defended my HdR in November 2016 on robust combinatorial optimization. I have been awarded the Robert Faure prize in 2018.

Research interests

My research interest lies at the junction of combinatorial optimization and mathematical optimization. I study theoretical properties (complexity, approximation) and numerical properties (exact algorithms) of optimization problems motivated by real applications (telecommunications, electrical power, production, transportation, ...). I am more particularly interested in the interplay between uncertainty and discrete optimization.

PhD Students

  • Adrien Cambier (2017 - ...)
  • Ikram Bouras (2016 - 2019)
  • Marco Silva (2015 - 2018)
  • Marcio Costa Santos (2013 - 2016)

Post-doc

  • Aniket Basu Roy (2018-2019)

Open Journal of Mathematical Optimization (OJMO)

We have created a free open-access journal in mathematical optimization: OJMO. The purpose of the journal is to provide a platform for publishing high-quality mathematical optimization research, free of charges for the authors and for the readers.


"Hannan Luss"    2019   

Journal articles1 document

  • Marcio Santos, Hannan Luss, Dritan Nace, Michael Poss. Proportional and maxmin fairness for the sensor location problem with chance constraints. Discrete Applied Mathematics, Elsevier, 2019, 261 (31), pp.316-331. ⟨10.1016/j.dam.2019.03.004⟩. ⟨hal-02088446⟩