Workshop

Discrete Optimization is the key to solving many problems from a broad spectrum of industrial and other applications. Moreover, Discrete Optimization is also linked to the recently flourishing area of Machine Learning. Efficient decomposition techniques as well as sophisticated combinatorial algorithms have been key ingredients to the success of the applicability of Discrete Optimization to realworld problems. Problem instances that, years ago, were judged intractable due to their size and the complexity of the underlying problem can now be solved.

During the workshop, internationally recognized leading scientists will introduce to state-of-the art techniques from different areas of Discrete Optimization and discuss recent advances as well as challenges. In addition to traditional approaches from scheduling and Dantzig-Wolfe decomposition there will be presentations about the interconnection between Discrete Optimization and Machine Learning.

The objective of the Felix Klein Academy autumn workshop is to introduce to important techniques, stipulate research and to discuss applications as well as the impact on real-world problems.

Speaker:

• Prof. Marco Lübbecke, RWTH Aachen
• Prof. Sebastian Pokutta, ZIB und TU Berlin
• Prof. René Sitters, Vrije Universiteit, Amsterdam

Program

25th September: Prof. Sebastian Pokutta, ZIB and TU Berlin

• 9:00 - 11:00: Discrete Optimization and Machine Learning
• 11:00 - 12:30: Current Challenges at the Interface of Discrete Optimization and Machine Learning

26th September: Prof. Marco Lübbecke, RWTH Aachen University

• 9:00 - 11:00: Branch-Price-and-Cut for the Impatient
• 11:00 - 12:30: Automating Branch-Price-and-Cut: Structure is Everything 
  

27th September: Prof. René Sitters, Vrije Universiteit, Amsterdam

• 9:00 - 11:00: Complexity and Approximation of Scheduling Problems
• 11:00 - 12:30: Problem of Minimizing Average Job Completion Time