Awarded by the European Working Group on Stochastic Optimization
XIV Conference on Computational Management Science “Pricing, Risk and Optimization in Management Science” Bergamo, Italy, May 30-June 1, 2017.
Jury for the CMS 2017 Student Best Paper Prize: Miloš Kopa, Daniel Kuhn, Francesca Maggioni and Rüdiger Schultz
First Place Winner: Jianzhe Zhen, “Adjustable Robust Optimization via Fourier-Motzkin Elimination”
Runners up:
- Julien Keutchayan, “Quality Evaluation of Scenario-Tree Generation Methods for Solving Stochastic Programming Problems”
- Rui Gao, “Data-driven Distributionally Robust Stochastic Optimization with Fixed Marginals”
XV Conference on Computational Management Science, Trondheim, Norway, 29-31 May 2018
Jury for the CMS 2018 Student Best Paper Prize: Miloš Kopa, Daniel Kuhn, Francesca Maggioni and Afzal Siddiqui
First Place Winner: Jonas Ekblom, “Stochastic optimization with importance sampling: using an analytical approximation of the zero-variance distribution”
Runners up:
- Grzegorz Marcjasz, “Electricity price forecasting with NARX networks: Is it better to combine point or probabilistic forecasts?”
- Simon Risanger, “A strategic investment model for multinational transmission expansion planning: Comparing competitive and cooperative solutions for a North Sea Offshore Grid”
XVI Conference on Computational Management Science, Chemnitz, 27-29 March 2019
Jury for the CMS 2019 Student Best Paper Prize: Francesca Maggioni and Werner Römisch
First Place Winner: Regan Baucke, “A deterministic algorithm for stochastic minimax dynamic programmes”
European Conference on Stochastic Optimization – XVII Computational Management Science, Venice, Italy, 29-30 June - 1 July 2022
Jury for the CMS 2022 Student Best Paper Prize: Stein-Erik Fleten, Miloš Kopa, Francesca Maggioni and Rüdiger Schultz
First Place Winner: Maël Forcier “Exact quantization of multistage stochastic problems”
Runners up:
- Bahar Taşkesen, “Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution”
- Adrián Esteban-Pérez, “Distributionally robust stochastic programs with side information based on trimmings”
