OeGOR Summer-School for PhD-candidates and Post-Docs, Krems (Austria)
The Austrian Society for Operations Research (OeGOR) organizes for the fourth time a summer-school for PhD-candidates and Post-Docs in cooperation with the Department for Economy and Health of the University for Continuing Education.
Invited Speakers:
Christina Büsing (RWTH Aachen): Dealing with uncertainty: robustness in combinatorial optimization
Tobias Harks (Uni Passau): Pricing in Resource Allocation Games
Date: 28.7.2025 – 1.8.2025
Place: University for Continuing Education (Donau Uni) Krems
Participation in the school is free of charge, if your institution or supervisor are members of OeGOR or of an OR-Society in a neighboring country. However, lunch will be organized centrally, thus requiring a meal contribution of € 60.- (nonrefundable) to be paid until 20.6.2025. All other food, travel and hotel arrangements must be organized and covered by the participants.
Registration: send an e-mail until May 16, 2025 (mentioning any dietary restrictions) to raimund.kovacevic@donau-uni.ac.at .
Each invited speaker will give a two-day program. The participants are also invited to give a presentation of their work. Take the chance to create a bond with fellow students and with OeGOR!
28.7.-29.7. Tobias Harks: Pricing in Resource Allocation Games
In this summer school I will present a quite general framework for pricing resources in order to induce desirable resource consumption profiles by selfish players. The theory is based on Lagrangian duality and I will show that the framework can help to unify several largely independent streams in the literature – tolls in transportation systems, Walrasian market equilibria, trading networks, energy networks and congestion control in communication networks
Besides reproving existing results, we establish novel existence results by using methods from polyhedral combinatorics, global optimization and discrete convexity.
30.7.: Short presentations by the participants
31.7.-1.8. Christina Büsing: Dealing with uncertainty: robustness in combinatorial optimization
Uncertainties are everywhere in optimization problems: in the cost, in the weights or in the demand. Robust optimization is a classical way to include these uncertainties into the optimization process. A solution is called robust, if it remains feasible in every single realization of the uncertain parameters. Furthermore, we aim at minimizing the worst-case cost. This setting is suitable if we need a solution with a high guaranteed performance as it is the case for infrastructure development. In this summer school, we will consider different forms of robust optimization as strict robustness and two-stage robustness. We will analyze the complexity of the corresponding problems according to the most classical uncertainty sets. Especially for the so-called budget uncertainties, we will show that the robust version is as difficult as the problem without uncertainties. Finally, we will consider two-stage robust problems motivated by applications in health care.
The participants are invited to bring their own laptops with wifi-internet access (Eduroam or 4G/5G).