Optimized data exploration applied to the simulation of a chemical process. - Raoul Heese; Michal Walczak; Tobias Seidel; Norbert Asprion; Michael Bortz (Comput. Chem. Eng., 2019)

Solving Semi-infinite Optimization Problems with Quadratic Rate of Convergence. - Tobias Seidel (Fraunhofer Verlag, 2020)

A transformation-based discretization method for solving general semi-infinite optimization problems. - Jan Schwientek; Tobias Seidel; Karl-Heinz Küfer (Math. Methods Oper. Res., 2021)

Simultaneous simulation and optimization of multiple dividing wall columns. - Tobias Seidel; Lena-Marie Ränger; Thomas Grützner; Michael Bortz (Comput. Chem. Eng., 2022)

Solving continuous set covering problems by means of semi-infinite optimization. - Helene Krieg; Tobias Seidel; Jan Schwientek; Karl-Heinz Küfer (Math. Methods Oper. Res., 2022)

A Quantum Optimization Case Study for a Transport Robot Scheduling Problem. - Dominik Leib; Tobias Seidel; Sven Jäger 001; Raoul Heese; Caitlin Isobel Jones; Abhishek Awasthi; Astrid Elisa Niederle; Michael Bortz (CoRR, 2023)

A Decomposition Method for the Hybrid Quantum-Classical Solution of the Number Partitioning Problem. - Zongji Li; Tobias Seidel; Michael Bortz; Raoul Heese (CoRR, 2023)

A unified approach to inverse robust optimization problems. - Holger Berthold; Till Heller; Tobias Seidel (Math. Methods Oper. Res., 2024)

Combining discrete and continuous information for multi-criteria optimization problems. - Katrin Teichert; Tobias Seidel; Philipp Süss (Math. Methods Oper. Res., 2024)

Pareto-optimized Dividing Wall Columns for Ideal Mixtures and Influences of Deviations in Process Variables. - Lea Trescher; Lena-Marie Ränger; David Mogalle; Tobias Seidel; Michael Bortz; Thomas Grützner (Comput. Chem. Eng., 2025)

Efficient solution of the number partitioning problem on a quantum annealer: a hybrid quantum-classical decomposition approach. - Zongji Li; Tobias Seidel; Dominik Leib; Michael Bortz; Raoul Heese (J. Heuristics, 2025)