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Introduction to Derivative-Free Optimization

2009-04-16 Mathematics
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Release : 2009-04-16
Genre : Mathematics
Kind : eBook
Book Rating : 683/5 ( reviews)

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Book Synopsis Introduction to Derivative-Free Optimization by : Andrew R. Conn

Download or read book Introduction to Derivative-Free Optimization written by Andrew R. Conn. This book was released on 2009-04-16. Available in PDF, EPUB and Kindle. Book excerpt: The first contemporary comprehensive treatment of optimization without derivatives. This text explains how sampling and model techniques are used in derivative-free methods and how they are designed to solve optimization problems. It is designed to be readily accessible to both researchers and those with a modest background in computational mathematics.

Derivative-Free and Blackbox Optimization

2017-12-02 Mathematics
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Release : 2017-12-02
Genre : Mathematics
Kind : eBook
Book Rating : 134/5 ( reviews)

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Book Synopsis Derivative-Free and Blackbox Optimization by : Charles Audet

Download or read book Derivative-Free and Blackbox Optimization written by Charles Audet. This book was released on 2017-12-02. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I. Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead). Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region). Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures. Benchmarking techniques are also presented in the appendix.

Introduction to Derivative-free Optimization

2009-01-01 Mathematics
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Release : 2009-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 767/5 ( reviews)

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Book Synopsis Introduction to Derivative-free Optimization by : Andrew R. Conn

Download or read book Introduction to Derivative-free Optimization written by Andrew R. Conn. This book was released on 2009-01-01. Available in PDF, EPUB and Kindle. Book excerpt: The absence of derivatives, often combined with the presence of noise or lack of smoothness, is a major challenge for optimisation. This book explains how sampling and model techniques are used in derivative-free methods and how these methods are designed to efficiently and rigorously solve optimisation problems.

Computational Optimization, Methods and Algorithms

2011-06-17 Technology & Engineering
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Release : 2011-06-17
Genre : Technology & Engineering
Kind : eBook
Book Rating : 592/5 ( reviews)

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Book Synopsis Computational Optimization, Methods and Algorithms by : Slawomir Koziel

Download or read book Computational Optimization, Methods and Algorithms written by Slawomir Koziel. This book was released on 2011-06-17. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deterministic Global Optimization

2017-06-16 Computers
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Release : 2017-06-16
Genre : Computers
Kind : eBook
Book Rating : 999/5 ( reviews)

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Book Synopsis Deterministic Global Optimization by : Yaroslav D. Sergeyev

Download or read book Deterministic Global Optimization written by Yaroslav D. Sergeyev. This book was released on 2017-06-16. Available in PDF, EPUB and Kindle. Book excerpt: This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed. Theoretical considerations are illustrated through engineering applications. Extensive numerical testing of algorithms described in this book stretches the likelihood of establishing a link between mathematicians and practitioners. The authors conclude by describing applications and a generator of random classes of test functions with known local and global minima that is used in more than 40 countries of the world. This title serves as a starting point for students, researchers, engineers, and other professionals in operations research, management science, computer science, engineering, economics, environmental sciences, industrial and applied mathematics to obtain an overview of deterministic global optimization.

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