Surrogate Model-Based Engineering Design and Optimization
Surrogate Model-Based Engineering Design and Optimization

Author: Ping Jiang

Publisher: Springer Nature

Published: 2019-11-01

Total Pages: 240

ISBN-13: 9811507317

DOWNLOAD EBOOK

This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization. Surrogate or metamodels are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are constructed from available input parameter values and the corresponding output performance or quantities of interest (QOIs) to provide predictions based on the fitted or interpolated mathematical relationships. The book highlights a range of methods for ensembling surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a more “hands-on” manner.

Active Robust Optimization: Optimizing for Robustness of Changeable Products
Active Robust Optimization: Optimizing for Robustness of Changeable Products

Author: Shaul Salomon

Publisher: Springer

Published: 2019-07-06

Total Pages: 194

ISBN-13: 303015050X

DOWNLOAD EBOOK

This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a “changeable product,” the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these ‎with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.

Sensitivity Analysis and Robust Optimization
Sensitivity Analysis and Robust Optimization

Author: Jiyoung Im

Publisher:

Published: 2018

Total Pages: 97

ISBN-13:

DOWNLOAD EBOOK

In this thesis, we study the special case of linear optimization to show what may affect the sensitivity of the optimal value function under data uncertainty. In this special case, we show that the robust optimization problem with a locally smaller feasible region yields a more conservative robust optimal value than the one with a locally bigger feasible region. To achieve that goal, we use a geometric approach to analyze the sensitivity of the optimal value function for linear programming (LP) under data uncertainty. We construct a family of proper cones where the strict containment holds for any pair of cones in the family. We then form a family of LP problems using this family of cones constructed above; the feasible regions of each pair of LPs in the family holds strict containment, every LP in the family has the unique optimal solution at the vertex of the cone and has the same objective function, i.e., every LP in the family shares the same optimal solution and the same optimal value. We rewrite he LPs so that they reflect the given data uncertainty and perform local analysis near the optimal solutions where the local strict containment holds. Finally, we illustrate that an LP with a locally smaller feasible region is more sensitive than an LP with a locally bigger feasible region.

Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems

Author: Carlos Coello Coello

Publisher: Springer Science & Business Media

Published: 2007-08-26

Total Pages: 810

ISBN-13: 0387367977

DOWNLOAD EBOOK

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.

Concurrent Engineering in the 21st Century
Concurrent Engineering in the 21st Century

Author: Josip Stjepandić

Publisher: Springer

Published: 2015-01-30

Total Pages: 836

ISBN-13: 331913776X

DOWNLOAD EBOOK

Presenting the gradual evolution of the concept of Concurrent Engineering (CE), and the technical, social methods and tools that have been developed, including the many theoretical and practical challenges that still exist, this book serves to summarize the achievements and current challenges of CE and will give readers a comprehensive picture of CE as researched and practiced in different regions of the world. Featuring in-depth analysis of complex real-life applications and experiences, this book demonstrates that Concurrent Engineering is used widely in many industries and that the same basic engineering principles can also be applied to new, emerging fields like sustainable mobility. Designed to serve as a valuable reference to industry experts, managers, students, researchers, and software developers, this book is intended to serve as both an introduction to development and as an analysis of the novel approaches and techniques of CE, as well as being a compact reference for more experienced readers.

Multi-Objective Memetic Algorithms
Multi-Objective Memetic Algorithms

Author: Chi-Keong Goh

Publisher: Springer Science & Business Media

Published: 2009-02-26

Total Pages: 399

ISBN-13: 354088050X

DOWNLOAD EBOOK

The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.

Evolutionary Computation in Dynamic and Uncertain Environments
Evolutionary Computation in Dynamic and Uncertain Environments

Author: Shengxiang Yang

Publisher: Springer

Published: 2007-04-03

Total Pages: 614

ISBN-13: 3540497749

DOWNLOAD EBOOK

This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Multi-Objective Optimization in Chemical Engineering
Multi-Objective Optimization in Chemical Engineering

Author: Gade Pandu Rangaiah

Publisher: John Wiley & Sons

Published: 2013-03-20

Total Pages: 487

ISBN-13: 1118341686

DOWNLOAD EBOOK

For reasons both financial and environmental, there is a perpetual need to optimize the design and operating conditions of industrial process systems in order to improve their performance, energy efficiency, profitability, safety and reliability. However, with most chemical engineering application problems having many variables with complex inter-relationships, meeting these optimization objectives can be challenging. This is where Multi-Objective Optimization (MOO) is useful to find the optimal trade-offs among two or more conflicting objectives. This book provides an overview of the recent developments and applications of MOO for modeling, design and operation of chemical, petrochemical, pharmaceutical, energy and related processes. It then covers important theoretical and computational developments as well as specific applications such as metabolic reaction networks, chromatographic systems, CO2 emissions targeting for petroleum refining units, ecodesign of chemical processes, ethanol purification and cumene process design. Multi-Objective Optimization in Chemical Engineering: Developments and Applications is an invaluable resource for researchers and graduate students in chemical engineering as well as industrial practitioners and engineers involved in process design, modeling and optimization.