Tutorial on goat, the basics of optimization and local vs. global optimization

We've completed a first tutorial on the use of goat and on optimization in general. We focus on a hands-on introduction to optimization. In particular, we elaborate on the differences between local and global optimization. After this tutorial, you will be able to use goat. Moreover, it will be made clear, how goat complements Galapagos.

Follow the complete tutorial at http://www.rechenraum.com/goat/tutorials.html.

Summary: For solving a general optimization problem, it is useful to follow a two-step procedure: First, a global optmization step (either goat or Galapagos) searches the entire parametric model space and identifies an intermediate solution close to the global optimum. Then, in a local optimization step with goat, this intermediate solution is fine-tuned to the final result.

Let me know if you have questions and/or comments!