Overview
- Editors:
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Slawomir Koziel
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Engineering Optimization & Modeling Center, School of Science & Engineering, Reykjavik University, Reykjavik, Iceland
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Leifur Leifsson
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Engineering Optimization & Modeling Center, School of Science & Engineering, Reykjavik University, Reykjavik, Iceland
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Xin-She Yang
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School of Science and Technology, Middlesex University, London, United Kingdom
- Covers new methods in surrogate-based optimization techniques
- Contributions examine engineering and scientific applications of various methods
- Of interest to researchers studying optimization techniques as well as engineers and other practitioners
- Includes supplementary material: sn.pub/extras
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Table of contents (14 papers)
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Front Matter
Pages i-viii
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- Thomas Slawig, Malte Prieß, Claudia Kratzenstein
Pages 1-24
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- Slawomir Koziel, Leifur Leifsson
Pages 25-51
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- Slawomir Koziel, Adrian Bekasiewicz, Piotr Kurgan
Pages 53-86
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- Leifur Leifsson, Slawomir Koziel, Piotr Kurgan
Pages 87-111
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- Adrian Bekasiewicz, Slawomir Koziel, Wlodzimierz Zieniutycz
Pages 113-147
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- Slawomir Koziel, Stanislav Ogurtsov
Pages 149-170
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- Abdel-Karim S. O. Hassan, Hany L. Abdel-Malek, Ahmed S. A. Mohamed
Pages 171-194
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- Piotr Kurgan, Adrian Bekasiewicz
Pages 195-218
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- Shi Cheng, T. O. Ting, Xin-She Yang
Pages 241-253
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- Chin Wei Bong, Xin-She Yang
Pages 255-268
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- Christoph Waldhauser, Ronald Hochreiter, Johannes Otepka, Norbert Pfeifer, Sajid Ghuffar, Karolina Korzeniowska et al.
Pages 269-292
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- Abhishek Awasthi, Jörg Lässig, Oliver Kramer
Pages 293-314
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- Keith Worden, Graeme Manson, Elizabeth J. Cross
Pages 315-335
About this book
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.
