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Surrogate-Based Modeling and Optimization

Surrogate-Based Modeling and Optimization
Author: Slawomir Koziel
Publisher: Springer Science & Business Media
Total Pages: 412
Release: 2013-06-06
Genre: Mathematics
ISBN: 1461475511

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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 volume features 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.


Simulation-Driven Modeling and Optimization

Simulation-Driven Modeling and Optimization
Author: Slawomir Koziel
Publisher: Springer
Total Pages: 404
Release: 2016-02-12
Genre: Mathematics
ISBN: 3319275178

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This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the efficiency of the simulation-driven design process. High-fidelity simulation models allow for accurate evaluations of the devices and systems, which is critical in the design process, especially to avoid costly prototyping stages. Despite this and other advantages, the use of simulation tools in the design process is quite challenging due to associated high computational cost. The steady increase of available computational resources does not always translate into the shortening of the design cycle because of the growing demand for higher accuracy and necessity to simulate larger and more complex systems. For this reason, automated simulation-driven design—while highly desirable—is difficult when using conventional numerical optimization routines which normally require a large number of system simulations, each one already expensive.


Simulation-Based Optimization

Simulation-Based Optimization
Author: Abhijit Gosavi
Publisher: Springer
Total Pages: 508
Release: 2014-10-30
Genre: Business & Economics
ISBN: 1489974911

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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.


Antenna Design by Simulation-Driven Optimization

Antenna Design by Simulation-Driven Optimization
Author: Slawomir Koziel
Publisher: Springer Science & Business Media
Total Pages: 141
Release: 2014-02-12
Genre: Mathematics
ISBN: 3319043676

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This Brief reviews a number of techniques exploiting the surrogate-based optimization concept and variable-fidelity EM simulations for efficient optimization of antenna structures. The introduction of each method is illustrated with examples of antenna design. The authors demonstrate the ways in which practitioners can obtain an optimized antenna design at the computational cost corresponding to a few high-fidelity EM simulations of the antenna structure. There is also a discussion of the selection of antenna model fidelity and its influence on performance of the surrogate-based design process. This volume is suitable for electrical engineers in academia as well as industry, antenna designers and engineers dealing with computationally-expensive design problems.


Computing Tools for Modeling, Optimization and Simulation

Computing Tools for Modeling, Optimization and Simulation
Author: Manuel Laguna
Publisher: Springer Science & Business Media
Total Pages: 318
Release: 2012-12-06
Genre: Business & Economics
ISBN: 1461545676

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Computing Tools for Modeling, Optimization and Simulation reflects the need for preserving the marriage between operations research and computing in order to create more efficient and powerful software tools in the years ahead. The 17 papers included in this volume were carefully selected to cover a wide range of topics related to the interface between operations research and computer science. The volume includes the now perennial applications of rnetaheuristics (such as genetic algorithms, scatter search, and tabu search) as well as research on global optimization, knowledge management, software rnaintainability and object-oriented modeling. These topics reflect the complexity and variety of the problems that current and future software tools must be capable of tackling. The OR/CS interface is frequently at the core of successful applications and the development of new methodologies, making the research in this book a relevant reference in the future. The editors' goal for this book has been to increase the interest in the interface of computer science and operations research. Both researchers and practitioners will benefit from this book. The tutorial papers may spark the interest of practitioners for developing and applying new techniques to complex problems. In addition, the book includes papers that explore new angles of well-established methods for problems in the area of nonlinear optimization and mixed integer programming, which seasoned researchers in these fields may find fascinating.


Simulation-Driven Design Optimization and Modeling for Microwave Engineering

Simulation-Driven Design Optimization and Modeling for Microwave Engineering
Author: Slawomir Koziel
Publisher: World Scientific
Total Pages: 526
Release: 2013
Genre: Technology & Engineering
ISBN: 1848169175

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On the other hand, various interactions between microwave devices and their environment, such as feeding structures and housing, must be taken into account, and this is only possible through full-wave EM analysis. Electromagnetic simulations can be highly accurate, but they tend to be computationally expensive. Therefore, practical design optimization methods have to be computationally efficient, so that the number of CPU-intensive high-fidelity EM simulations is reduced as much as possible during the design process. For the same reasons, techniques for creating fast yet accurate models of microwave structures become crucially important. In this edited book, the authors strive to review the state-of-the-art simulation-driven microwave design optimization and modeling. A group of international experts specialized in various aspects of microwave computer-aided design summarize and review a wide range of the latest developments and real-world applications.


High-Performance Simulation-Based Optimization

High-Performance Simulation-Based Optimization
Author: Thomas Bartz-Beielstein
Publisher: Springer
Total Pages: 291
Release: 2019-06-01
Genre: Technology & Engineering
ISBN: 3030187640

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This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.


Handbook of Simulation Optimization

Handbook of Simulation Optimization
Author: Michael C Fu
Publisher: Springer
Total Pages: 387
Release: 2014-11-13
Genre: Business & Economics
ISBN: 1493913840

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The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.


Modeling, Simulation, and Optimization

Modeling, Simulation, and Optimization
Author: Pandian Vasant
Publisher: Springer
Total Pages: 129
Release: 2017-12-07
Genre: Technology & Engineering
ISBN: 3319705423

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This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume. Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016; Includes research into soft computing and its application in engineering and technology; Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.


Simulation-Driven Aerodynamic Design Using Variable-Fidelity Models

Simulation-Driven Aerodynamic Design Using Variable-Fidelity Models
Author: Leifur Leifsson
Publisher: World Scientific
Total Pages: 444
Release: 2015-01-09
Genre: Technology & Engineering
ISBN: 1783266309

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Computer simulations is a fundamental tool of the design process in many engineering disciplines including aerospace engineering. However, although high-fidelity numerical models are accurate, they can be computationally expensive with evaluation time for a single design as long as hours, days or even weeks. Simulation-driven design using conventional optimization techniques may be therefore prohibitive. This book explores the alternative: performing computationally efficient design using surrogate-based optimization, where the high-fidelity model is replaced by its computationally cheap but still reasonably accurate representation: a surrogate. The emphasis is on physics-based surrogates. Application-wise, the focus is on aerodynamics and the methods and techniques described in the book are demonstrated using aerodynamic shape optimization cases. Applications in other engineering fields are also demonstrated. State-of-the-art techniques and a depth of coverage never published before make this a unique and essential book for all researchers working in aerospace and other engineering areas and dealing with optimization, computationally expensive design problems, and simulation-driven design. Contents:Motivation and Problem Formulation:IntroductionAerodynamic Shape OptimizationOptimization Techniques:Simulation-Driven Design: Direct MethodsSurrogate-Based OptimizationSBO with Approximation-Based SurrogatesSBO with Physics-Based SurrogatesAerodynamics Modeling:Geometry ParameterizationHigh-Fidelity Aerodynamic ModelsLow-Fidelity Aerodynamics ModelsApplications:Transonic Airfoil Shape DesignTransonic Wing Shape DesignSubsonic Shape DesignSelected Applications of Surrogate-Based Optimization in Other AreasSurrogate-Based Optimization with MATLABConclusion:Practical Aspects of Variable-Fidelity Design Readership: Graduate students and researchers in the field of engineering, in particular, aerospace engineering. Key Features:Gathers a number of relevant techniques that were never compiled in one publication before, and certain state-of-the-art techniques have never been published in book formCompact and self-contained introduction to the area of surrogate-based optimization and variable-fidelity optimizationAt present, this is the only book available on the market that offers coverage of variable-fidelity optimization methodsKeywords:Aerodynamic Shape Optimization;Computational Fluid Dynamics (CFD);Surrogate Modeling;Surrogate-based Optimization;Variable-fidelity Simulations;Simulation-driven Design