The book provides suggestions on how to start using bionic optimization methods including
pseudo-code examples of each of the important approaches and outlines of how to improve them.
The most efficient methods for accelerating the studies are discussed. These include the
selection of size and generations of a study's parameters modification of these driving
parameters switching to gradient methods when approaching local maxima and the use of
parallel working hardware.Bionic Optimization means finding the best solution to a problem
using methods found in nature. As Evolutionary Strategies and Particle Swarm Optimization seem
to be the most important methods for structural optimization we primarily focus on them. Other
methods such as neural nets or ant colonies are more suited to control or process studies so
their basic ideas are outlined in order to motivate readers to start using them.A set of sample
applications shows how Bionic Optimization works inpractice. From academic studies on simple
frames made of rods to earthquake-resistant buildings readers follow the lessons learned
difficulties encountered and effective strategies for overcoming them. For the problem of tuned
mass dampers which play an important role in dynamic control changing the goal and
restrictions paves the way for Multi-Objective-Optimization. As most structural designers today
use commercial software such as FE-Codes or CAE systems with integrated simulation modules
ways of integrating Bionic Optimization into these software packages are outlined and examples
of typical systems and typical optimization approaches are presented.The closing section
focuses on an overview and outlook on reliable and robust as well as on
Multi-Objective-Optimization including discussions of current and upcoming research topics in
the field concerning a unified theory for handling stochastic design processes.
