Optimization and Computational Fluid Dynamics
Optimization and Computational Fluid Dynamics

Author: Dominique Thévenin

Publisher: Springer Science & Business Media

Published: 2008-01-08

Total Pages: 301

ISBN-13: 3540721533

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The numerical optimization of practical applications has been an issue of major importance for the last 10 years. It allows us to explore reliable non-trivial configurations, differing widely from all known solutions. The purpose of this book is to introduce the state-of-the-art concerning this issue and many complementary applications are presented.

Computational Optimization, Methods and Algorithms
Computational Optimization, Methods and Algorithms

Author: Slawomir Koziel

Publisher: Springer Science & Business Media

Published: 2011-06-17

Total Pages: 292

ISBN-13: 3642208584

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Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Quantification of Uncertainty: Improving Efficiency and Technology
Quantification of Uncertainty: Improving Efficiency and Technology

Author: Marta D'Elia

Publisher: Springer Nature

Published: 2020-07-30

Total Pages: 290

ISBN-13: 3030487210

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This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.

Bayesian Optimization
Bayesian Optimization

Author: Roman Garnett

Publisher: Cambridge University Press

Published: 2023-01-31

Total Pages: 376

ISBN-13: 1108623557

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Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond. This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way. This bottom-up approach illuminates unifying themes in the design of Bayesian optimization algorithms and builds a solid theoretical foundation for approaching novel situations. The core of the book is divided into three main parts, covering theoretical and practical aspects of Gaussian process modeling, the Bayesian approach to sequential decision making, and the realization and computation of practical and effective optimization policies. Following this foundational material, the book provides an overview of theoretical convergence results, a survey of notable extensions, a comprehensive history of Bayesian optimization, and an extensive annotated bibliography of applications.

Simulation-Driven Modeling and Optimization
Simulation-Driven Modeling and Optimization

Author: Slawomir Koziel

Publisher: Springer

Published: 2016-02-12

Total Pages: 405

ISBN-13: 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.

TEXTBOOK OF COMPUTER AIDED DRUG DEVELOPMENT
TEXTBOOK OF COMPUTER AIDED DRUG DEVELOPMENT

Author: Prof. (Dr.) Keerthi. G. S. Nair

Publisher: Shashwat Publication

Published: 2024-08-07

Total Pages: 308

ISBN-13: 9360874833

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This book delves into the utilization of computer-assisted techniques in the exploration, design, optimization, and production of novel pharmaceutical formulations and drug delivery systems, with a focus on their efficacy and safety. It covers computational methods, statistical and molecular modeling, all aimed at facilitating the development and safe administration of drugs in humans. The integration of Quality by Design (QbD), Design of Experiments (DoE), artificial intelligence, and in silico pharmacokinetic assessment/simulation is greatly facilitated by commercial software and expert systems, all of which are thoroughly examined in this title, accompanied by examples drawn from recent research. "Computer-aided Pharmaceutics and Drug Delivery" serves as a comprehensive reference for the latest scholarly updates on emerging developments in computer-assisted techniques for drug design and development. It is tailored for pharmacists, medical practitioners, students, and researchers seeking authoritative insights into this evolving field.

Metaheuristics in Water, Geotechnical and Transport Engineering
Metaheuristics in Water, Geotechnical and Transport Engineering

Author: Xin-She Yang

Publisher: Newnes

Published: 2012-09

Total Pages: 503

ISBN-13: 0123982960

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Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are often large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems. This book examines the latest developments of metaheuristics and their applications in water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks. This book can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheursitics, optimization in civil engineering and computational intelligence. Provides detailed descriptions of all major metaheuristic algorithms with a focus on practical implementation Develops new hybrid and advanced methods suitable for civil engineering problems at all levels Appropriate for researchers and advanced students to help to develop their work