  Numerical optimization of complex systems benefits from the technological
development of computing platforms in the last twenty years. Unfortunately,
this is still not enough, and a large computational time is still necessary
when mathematical models that include richer (and therefore more realistic)
physical models are adopted.
  In this paper we show how the combination of optimization and Artificial
Intelligence (AI), in particular the Machine Learning algorithms, can help in
strongly reducing the overall computational times, making possible the use of
complex simulation systems within the optimization cycle. Original approaches
are also proposed.

Optimization and Control