Classes
- Computational Aspects of OptimisationNMEK436 | Faculty of Mathematics and Physics
- Introduction to Optimisation +1NMFM204 | Faculty of Mathematics and Physics
- Colloquium of the Department of Probability and Mathematical StatisticsNMSA600 | Faculty of Mathematics and Physics
- Advanced Topics of the FieldNMSA603 | Faculty of Mathematics and Physics
- Introduction to Optimisation (M)NMSA936 | Faculty of Mathematics and Physics
Publications
- Sample approximation technique for mixed-integer stochastic programming problems with expected value constraints2014 | Faculty of Mathematics and Physics
- Sample approximation techniques for DEA-risk efficiency tests2014 | Faculty of Mathematics and Physics
- Influence of short sales and margin requirements on portfolio efficiency - a DEA-risk approach2014 | Faculty of Mathematics and Physics
- Approximation and contamination bounds for probabilistic programs +12012 | Faculty of Mathematics and Physics
- Stochastic programming problems with generalized integrated chance constraints2012 | Faculty of Mathematics and Physics
- Sample approximation technique for mixed-integer stochastic programming problems with several chance constraints2012 | Faculty of Mathematics and Physics
- Chance constrained problems: penalty reformulation and performance of sample approximation technique2012 | Faculty of Mathematics and Physics
- Solving real-life portfolio problem using stochastic programming and Monte-Carlo techniques2010 | Faculty of Mathematics and Physics
- Nonconvex stochastic programming problems - formulations, sample approximations and stabilityPublication without faculty affiliation
- Value at risk approach to producer's best response in an electricity market with uncertain demand2023 | Faculty of Mathematics and Physics
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