The Tilburg Center for Optimization aims to develop new optimization models and methods and to solve practical optimization problems in industry and governmental institutes.

Ticopt For Companies

Ticopt can offer you:
  • Assistance in modeling and solving advanced optimization problems
  • In-house training and advice on optimization topics
  • Ticopts offers several courses (1 day) on optimization topics


Robust optimization

Many optimization problems contain uncertain parameters, e.g. due to estimation or implementation errors. Robust optimization started in the late 90's and is now a promising methodology to find optimal solutions that are robust against the uncertainties in the problem.

Mixed-integer nonlinear optimization

Many optimization problems contain both nonlinear constraints and integer variables. Methods for MINLP have been improved a lot in the last decade. These new efficient methods enable us to solve real-life MINLP problems.

Simulation-based optimization

Simulation tools are often used in practice in many fields: engineering, logistics, finance, etc. In practice, often one not only simulates, but also optimizes by performing different simulation runs. Most often a simulation run is time-expensive and one would like to optimize by performing a minimal number of simulation runs. New optimization methods have been developed to perform this task.

Conic optimization

Conic optimization is a new trend in convex optimization. It extends the class of linear programming problems. Many practical problems that cannot be modeled as linear programming problems can be modeled as conic optimization problems, as Conic Quadratic Programming or Semi-Definite programming problems. Nowadays there are efficient solvers to solve large dimensional conic optimization problems. Especially Conic Quadratic Problems can be solved almost as efficient as linear programming problems.
For more information about these courses please contact Ruud Brekelmans or Dick den Hertog .