Prof. Dr. Andreas Schulz, Daniel Vaz
NP-complete optimization problems cannot be solved in polynomial time (unless P=NP). One way to obtain efficient algorithms anyway is to relax optimality. An approximation algorithm is an algorithm that runs in polynomial time and computes a feasible solution with an objective function value that is within a certain factor of that of an optimal solution. This seminar covers recent results as well as advanced techniques in the field. Participants are assigned research papers and are expected to deliver a presentation, demonstrating in-depth understanding of the discussed problem, key technical ideas and proofs, related bibliography, and open questions.
The presentations will take place in English.
Discrete Optimization (MA3502) or Combinatorial Optimization (MA4502)
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