19240411 Seminar

SoSe 19: Algorithmic Mixed-Integer Programming

Timo Berthold

Additional information / Pre-requisites

Location and schedule:

  • first meeting (introduction and paper assignment): April 18, 10:00-12:00, ZIB (Takustr. 7), Seminar room 2006 (ground floor)
  • second meeting (short talk): May 23, 10:00-12:00, ZIB (Takustr. 7), Seminar room 2006 (ground floor) TBA on day in midterm
  • final meeting (seminar talk): TBA on one or two days at the end of the semester

Students should have some background in mathematical optimization including basic graph theory and basic linear programming.

In the middle of the term, you are supposed to give a short, introductory talk (at most 5 minutes) on your topic.

To obtain the credit points, you are also required to hand in a short summary of your talk (use LaTeX, 5-8 pages). The summary should be sent by e-mail to your advisor. The summary will be graded and then handed back to you. We hope that this feedback will enable you to give a better presentation.

The seminar itself will take place on one or two days in the last weeks of the semester. Talks should be prepared for 45 minutes, so that a duration of 60 minutes including questions is not exceeded. Having submitted the summary is a requirement for participation.

Your final grade will be composed of 60% and 40% from the evaluation of your talk and paper, respectively.

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Content:

In the seminar "Algorithmic Mixed-Integer Programming" we will study the literature on mathematical optimization algorithms that form the basis for the computational state of the art in mixed-integer optimization today. This includes fundamental papers on solving linear programming relaxations, branch-and-cut, primal heuristics, exact presolving reductions, infeasibility analysis, and the more recent techniques to make use of machine learning to accelerate the solution process. After this seminar, students will have gained insight into the computationally most important algorithms behind today's MIP solver software and will be competent to analyze their computational behavior.

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