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Books > Science & Mathematics > Mathematics > Optimization
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Solving Computationally Expensive Engineering Problems - Methods and Applications (Hardcover, 2014 ed.)
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Solving Computationally Expensive Engineering Problems - Methods and Applications (Hardcover, 2014 ed.)
Series: Springer Proceedings in Mathematics & Statistics, 97
Expected to ship within 10 - 15 working days
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Computational complexity is a serious bottleneck for the design
process in virtually any engineering area. While migration from
prototyping and experimental-based design validation to
verification using computer simulation models is inevitable and has
a number of advantages, high computational costs of accurate,
high-fidelity simulations can be a major issue that slows down the
development of computer-aided design methodologies, particularly
those exploiting automated design improvement procedures, e.g.,
numerical optimization. The continuous increase of available
computational resources does not always translate into shortening
of the design cycle because of the growing demand for higher
accuracy and necessity to simulate larger and more complex systems.
Accurate simulation of a single design of a given system may be as
long as several hours, days or even weeks, which often makes design
automation using conventional methods impractical or even
prohibitive. Additional problems include numerical noise often
present in the simulation data, possible presence of multiple
locally optimum designs, as well as multiple conflicting
objectives. In this edited book, various techniques that can
alleviate solving computationally expensive engineering design
problems are presented. One of the most promising approaches is the
use of fast replacement models, so-called surrogates, that reliably
represent the expensive, simulation-based model of the
system/device of interest but they are much cheaper and
analytically tractable. Here, a group of international experts
summarize recent developments in the area and demonstrate
applications in various disciplines of engineering and science. The
main purpose of the work is to provide the basic concepts and
formulations of the surrogate-based modeling and optimization
paradigm, as well as discuss relevant modeling techniques,
optimization algorithms and design procedures. Therefore, this book
should be useful to researchers and engineers from any discipline
where computationally heavy simulations are used on daily basis in
the design process.
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