This SpringerBrief bridges the gap between the areas of simulation
studies on the one hand, and optimization with natural computing on the
other. Since natural computing methods have been applied with great
success in several application areas, a review concerning potential
benefits and pitfalls for simulation studies is merited. The brief
presents such an overview and combines it with an introduction to
natural computing and selected major approaches, as well as with a
concise treatment of general simulation-based optimization. As such, it
is the first review which covers both the methodological background and
recent application cases.
The brief is intended to serve two purposes: First, it can be used to
gain more information concerning natural computing, its major dialects,
and their usage for simulation studies. It also covers the areas of
multi-objective optimization and neuroevolution. While the latter is
only seldom mentioned in connection with simulation studies, it is a
powerful potential technique. Second, the reader is provided with an
overview of several areas of simulation-based optimization which range
from logistic problems to engineering tasks. Additionally, the brief
focuses on the usage of surrogate and meta-models. The brief presents
recent application examples.