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Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.    This book is about surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Reliability (Engineering) -- Congresses . --- Computer science --- Mathematical optimization --- Engineering & Applied Sciences --- Applied Mathematics --- Mathematics --- Engineering models. --- Engineering economy. --- Economy, Engineering --- Engineering economics --- Engineering --- Similitude in engineering --- Models --- Mathematics. --- Computer mathematics. --- Mathematical models. --- Calculus of variations. --- Operations research. --- Management science. --- Aerospace engineering. --- Astronautics. --- Control engineering. --- Mathematical Modeling and Industrial Mathematics. --- Aerospace Technology and Astronautics. --- Control. --- Calculus of Variations and Optimal Control; Optimization. --- Operations Research, Management Science. --- Computational Mathematics and Numerical Analysis. --- Industrial engineering --- Models and modelmaking --- Mathematical optimization. --- Control and Systems Theory. --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Space sciences --- Aeronautics --- Astrodynamics --- Space flight --- Space vehicles --- Quantitative business analysis --- Management --- Problem solving --- Statistical decision --- Operational analysis --- Operational research --- Management science --- Research --- System theory --- Isoperimetrical problems --- Variations, Calculus of --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Aeronautical engineering --- Astronautics --- Models, Mathematical

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Contemporary engineering design is heavily based on computer simulations. Accurate, high-fidelity simulations are used not only for design verification but, even more importantly, to adjust parameters of the system to have it meet given performance requirements. Unfortunately, accurate simulations are often computationally very expensive with evaluation times as long as hours or even days per design, making design automation using conventional methods impractical. These and other problems can be alleviated by the development and employment of so-called surrogates that reliably represent the expensive, simulation-based model of the system or device of interest but they are much more reasonable and analytically tractable.    This book is about surrogate-based modeling and optimization techniques, and their applications for solving difficult and computationally expensive engineering design problems. It begins by presenting the basic concepts and formulations of the surrogate-based modeling and optimization paradigm and then discusses relevant modeling techniques, optimization algorithms and design procedures, as well as state-of-the-art developments. The chapters are self-contained with basic concepts and formulations along with applications and examples. The book will be useful to researchers in engineering and mathematics, in particular those who employ computationally heavy simulations in their design work.

Numerical methods of optimisation --- Operational research. Game theory --- Mathematical statistics --- Mathematics --- Space research --- Astronomy --- Engineering sciences. Technology --- Planning (firm) --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- astronauten --- informatica --- mathematische modellen --- externe fixatie (geneeskunde --- controleleer --- econometrie --- wiskunde --- operationeel onderzoek --- kansrekening --- ruimtevaart --- optimalisatie

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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.

Engineering mathematics --- Engineering design --- Mathematical optimization --- Data processing. --- Mathematical models. --- Mathematical optimization. --- Optimization. --- Mathematical Modeling and Industrial Mathematics. --- Discrete Optimization. --- Continuous Optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Models, Mathematical

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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.

Numerical methods of optimisation --- Operational research. Game theory --- Mathematics --- Planning (firm) --- Computer. Automation --- automatisering --- mathematische modellen --- wiskunde

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This book includes extended and revised versions of a set of selected papers from the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2013) which was co-organized by the Reykjavik University (RU) and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC). SIMULTECH 2013 was held in cooperation with the ACM SIGSIM - Special Interest Group (SIG) on SImulation and Modeling (SIM), Movimento Italiano Modellazione e Simulazione (MIMOS) and AIS Special Interest Group on Modeling and Simulation (AIS SIGMAS) and technically co-sponsored by the Society for Modeling & Simulation International (SCS), Liophant Simulation, Simulation Team and International Federation for Information Processing (IFIP). This proceedings brings together researchers, engineers, applied mathematicians and practitioners working in the advances and applications in the field of system simulation.

Engineering. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Simulation and Modeling. --- Artificial intelligence. --- Computer simulation. --- Ingénierie --- Intelligence artificielle --- Simulation par ordinateur --- Engineering & Applied Sciences --- Computer Science --- Computer simulation --- Mathematical models --- Models, Mathematical --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Simulation methods --- Model-integrated computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Soft computing --- Artificial Intelligence.