New Algorithmic Paradigms in Optimization

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This three week event is part of the two graduate programs at ETHZ:

• Graduate School of Mathematics in Discrete Mathematics and Optimization
  
• Cadmo: Graduate School of Computer Science in Algorithms, Discrete mathematics and Optimization.

The main topics of the event are the basic research directions of the last two decades in optimization. Several new mathematical methods emerged across various fields that at the moment seem to be matured to be efficiently applied in optimization. The methods we particularly would like to be presented on this meeting include:

• Geometric "Markov Chain Monte Carlo" methods applied to convex optimization and volume computation
• Semidefinite/cone programming and their applications to control theory and to polynomial, combinatorial, nonlinear and convex optimizations
• Lattice points computations and their applications to integer programming
• Various other novel approaches like smoothed analysis of the simplex method, quantum computing or bio-inspired algorithms.

Last updated: June 9, 2008