Discrete optimization as decision support

It is fascinating that mathematical models and algorithms can be used to compute and suggest a good course of action when faced with a decision so complex that it is difficult for a human to grasp all aspects of it. For me, our research is about pushing the limits for when optimization can be of practical use, both with respect to how a problem is modelled, and through the development of efficient solution strategies. My research is within discrete optimization, with a special interest in decomposition methods, and the applications are mainly within scheduling and resource allocation.

Professional activities
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Professional activities

  • Member of the Board of the Department of Mathematics, Linköping University, 2018 -
  • Member of the Programme Board for Electrical Engineering, Applied Physics and Computational Sciences, Linköping University, 2018 -
  • Specialist in Optimisation at Saab Aeronautics, 2014 -
  • Co-founder of Schemagi, 2009 -
  • President of the Swedish Operations Research Association, 2016 - 2019
    (member of the board since 2014)

Student theses

  • Optimisation of truck hauling schedules and passing bay locations in underground mines, Albin Ryberg, 2020

Current teaching

Research domain
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PhD students
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Former PhD students

  • Fred Mayambala, Makarere University, Uganda, 2012-2017,  (co-supervisor)

Thesis: Mean-Variance Portfolio Optimization: Eigendecomposition-Based Methods

  • Yixin Zhao, 2012-2016,  (co-supervisor)

Thesis: On the Integration of Heuristics with Column-Oriented Models for Discrete Optimization

Publications
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2020

2019

2018

2017

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Organisation
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