Dissertation theses usually deal with complex mathematical optimization problems for which no efficient solution methods exist so far. Often such optimization problems are motivated by practical applications in industry, economics or engineering sciences. The investigated optimization problems all contain the common structure of discrete decisions, i.e., either yes/no (0/1) decisions or integer numbers. Typically, such optimization tasks can be formulated via mixed-integer linear or nonlinear optimization problems (MIP or MINLP). A dissertation thesis usually includes the development of a solution method, based on a mathematical analysis of the corresponding mathematical structures. The solution methodology is mostly tested on real-world or realistic data.

• Sensitivity Analysis and Resilience of Integer Programs using the Example of Energy Systems
  Erik Jansen (Prof. Pfetsch)
• Mixed-Integer Nonlinear Optimization of Heating Networks
  Lea Rehlich (Prof. Pfetsch and Prof. Ulbrich)
• Incremental Maximization
  David Weckbecker (Prof. Disser)
• Online Graph Exploration
  Julia Baligacs (Prof. Disser)
• Potential-based Flows
  Annette Lutz (Prof. Disser)
• Complexity of the Simplex Method
  Nils Mosis (Prof. Disser)
• Robust Optimization of Energy Networks
  Jonas Alker (Prof. Pfetsch)
• Handling Symmetries in Maximum Stable Set Problems
  Annika Jäger (Prof. Pfetsch)
• Online Server Problems
  Linda Thelen (Prof. Disser)

• On the Proof Complexity of Linear Programming Based Branch-and-Bound
  Maximilian Gläser (Prof. Pfetsch) TUprints

• Competitive Analysis for Incremental Maximization
  David Michael Weckbecker (Prof. Disser) TUprints

• Sparse Recovery Under Side Constraints Using Null Space Properties (opens in new tab)
  Frederic Matter (Prof. Pfetsch)
• Interdiction Problems in Mixed-Integer Nonlinear Programming
  Andreas Schmitt (Prof. Pfetsch)

• Competitive analysis of the online dial-a-ride problem
  Alexander Birx (Prof. Disser)
• Mixed-Integer Optimization with Ordinary Differential Equations for Gas Networks (opens in new tab)
  Oliver Habeck (Prof. Pfetsch)
• The complexity of Zadeh's pivot rule
  Alexander Hopp (Prof. Disser)

• Computational Mixed-Integer Semidefinite Programming
  Tristan Gally (Prof. Pfetsch)
• Optimal Operation of Water Supply Networks by Mixed Integer Nonlinear Programming and Algebraic Methods (opens in new tab)
  Wei Huang (Prof. Pfetsch)

• Partitioning into Isomorphic or Connected Subgraph (opens in new tab)s
  Hendrik Lüthen (Prof. Pfetsch)
• Symmetries in Binary Programs – A Polyedral Perspective
  Christopher Hojny (Prof. Pfetsch)

• Branch-and-Cut for Complementarity and Cardinality Constrained Linear Programs (opens in new tab)
  Tobias Fischer (Prof. Pfetsch)

• Analyzing Infeasibility in Flow Networks
  Imke Joorman (Prof. Pfetsch)

• Computational Aspects of Compressed Sensing (opens in new tab)
  Andreas Tillmann (Prof. Pfetsch)