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Bionic Optimization in Structural Design - Stochastically Based Methods to Improve the Performance of Parts and Assemblies (Hardcover, 1st ed. 2016)
Loot Price: R3,234
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Bionic Optimization in Structural Design - Stochastically Based Methods to Improve the Performance of Parts and Assemblies (Hardcover, 1st ed. 2016)
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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 in practice. 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.
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