Optimization is the process that determines the optimal (best possible) solution to a problem - the optimum. Since the beginning of its existence, mankind has strived for what is best for it.

There are a huge number of articles on optimization - a branch of applied mathematics - because it can be used in so many different ways. Such methods are used in almost all economic decision-making processes as well as in many technical, scientific and engineering problems.

In this training course, we want to introduce the mathematical basics of this topic using some important aspects of optimization (non-linear optimization and optimization with neural networks). Participants will be able to try out the content taught in exercises using simple case studies.

The topic of optimization will be continued in the autumn with a further course. The focus will then be on graph algorithms and stochastic optimization.

Program

09.30 - 09.45	Welcome by Prof. Dr. W. Klotz
09.45 - 10.45	Introduction to non-linear optimization Dr. H. Behnke
10.45 - 11.15	Coffee break
11.15 - 12.15	Optimization with neural networks (Dr. M. Breitner)
12.15 - 13.30	Lunch break
13.30 - 14.30	Exercise (Part I)
14.30 - 15.00	Coffee break
15.00 - 16.00	Exercise (Part II)
16.00 - 16.30	Discussion and closing remarks