June 28, 2014

Computational Mixed-Integer Programming Workshop


In this one-week course, we offered a training in formulating linear, nonlinear, and mixed-integer optimization problems using the modeling language AMPL (https://ampl.com), and solving these problems with various problem-class specific numerical solvers. Optimization problems are at the core of various decision questions that modern industrial and service companies are facing every day. For example, finding an optimal product mix, an optimal schedule for workers, or an optimal allocation of scarce resources, are crucial for the survival of any firm operating in a competitive market environment. We assume that the participants are aware of some basic background in mathematical optimization techniques (for example, the simplex algorithm for linear programming, or branch-and-bound methods for integer programming).

The focus in this course lie on the transformation of a real-world problem into a mathematical formulation. Participants were expected to bring their own laptop (MacOS, Linux, Windows equally welcome).

The course offered a 3 hour lecture in the morning and a 3 hour practical training in the afternoon from Monday to Friday. On Saturday, we offered a written examination, upon which certificates were provided.

Short Bio Armin:

Armin Fügenschuh studied mathematics from 1995 to 2000 in Oldenburg, Germany, and at the Jagiellonian University in Cracow, Poland. In 2000,  he became a Research Associate at the Darmstadt University of Technology where he received a Doctorate degree (Dr. rer. nat.) in 2005. After that he held Post-Doc positions in Darmstadt, Berlin, Atlanta (Georgia, USA), and Erlangen. Between 2013 and 2017 he was an Associate Professor at the Helmut Schmidt University / University of the Federal Armed Forces in Hamburg. Since 2017 he is a full Professor for Engineering Mathematics and Numerics of optimization at the Brandenburg University of Technology in Cottbus.

Prof. Dr. Armin Fügenschuh’s main research interests are linear and nonlinear mixed-integer programming and their applications, in particular to problems from engineering, transportation, and logistics.

Short Bio Fabian:

Starting 2010 Fabian Gnegel studied at the University of Hamburg and finished with a BSc in Mathematics 2013. Afterwards he joined the Erasmus Mundus in Mathematical Modeling in Engineering a joint program of the University of L’Aquila, the Autonomous University of Barcelona, the University of Hamburg,  the University of Nice – Sophia Antipolis and the Gdańsk University of Technology, which he finished in 2015 with a Master of Science degree. From 2015 to 2017 at the Helmut Schmidt University / University of the Federal Armed Forces in Hamburg and since 2017 at the Brandenburg University of Technology in Cottbus Fabian Gnegel has been a Research Associate under the supervision of Armin Fügenschuh.

Fabian’s research focuses on time-dependent discrete decision processes with applications to the optimization of logistic systems.

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