2 citations · 2 across the 2 of their papers we have counts for
6 papers · 1 filter
Machine Learning for K-adaptability in Two-stage Robust Optimization
Esther Julien, Krzysztof Postek, Ş. İlker Birbil
Two-stage robust optimization problems constitute one of the hardest optimization problem classes. One of the solution approaches to this class of problems is K-adaptability. This…
An adaptive robust optimization model for parallel machine scheduling
Izack Cohen, Krzysztof Postek, Shimrit Shtern
Real-life parallel machine scheduling problems can be characterized by: (i) limited information about the exact task duration at scheduling time, and (ii) an opportunity to resched…
First-order algorithms for robust optimization problems via convex-concave saddle-point Lagrangian reformulation
Krzysztof Postek, Shimrit Shtern
Robust optimization (RO) is one of the key paradigms for solving optimization problems affected by uncertainty. Two principal approaches for RO, the robust counterpart method and t…
Global optimality in model predictive control via hidden invariant convexity
Jorn H. Baayen, Krzysztof Postek
Non-convex optimal control problems occurring in, e.g., water or power systems, typically involve a large number of variables related through nonlinear equality constraints. The id…
Piecewise constant decision rules via branch-and-bound based scenario detection for integer adjustable robust optimization
Ward Romeijnders, Krzysztof Postek
Multi-stage problems with uncertain parameters and integer decisions variables are among the most difficult applications of robust optimization (RO). The challenge in these problem…
Distributionally robust optimization with polynomial densities: theory, models and algorithms
Etienne de Klerk, Daniel Kuhn, Krzysztof Postek
In distributionally robust optimization the probability distribution of the uncertain problem parameters is itself uncertain, and a fictitious adversary, e.g., nature, chooses the…