Numerical Optimization

Numerical Optimization
Title Numerical Optimization PDF eBook
Author Jorge Nocedal
Publisher Springer Science & Business Media
Pages 686
Release 2006-12-11
Genre Mathematics
ISBN 0387400656

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Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Numerical Optimization Techniques for Engineering Design

Numerical Optimization Techniques for Engineering Design
Title Numerical Optimization Techniques for Engineering Design PDF eBook
Author Garret N. Vanderplaats
Publisher McGraw-Hill Companies
Pages 360
Release 1984
Genre Technology & Engineering
ISBN

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Numerical Optimization Techniques

Numerical Optimization Techniques
Title Numerical Optimization Techniques PDF eBook
Author I︠U︡riĭ Gavrilovich Evtushenko
Publisher
Pages 584
Release 1985
Genre Mathematical optimization
ISBN

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Numerical Optimization

Numerical Optimization
Title Numerical Optimization PDF eBook
Author Jorge Nocedal
Publisher Springer Science & Business Media
Pages 651
Release 2006-06-06
Genre Mathematics
ISBN 0387227423

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The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on methods best suited to practical problems. This edition has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are widely used in practice and are the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience.

Fundamentals of Optimization Techniques with Algorithms

Fundamentals of Optimization Techniques with Algorithms
Title Fundamentals of Optimization Techniques with Algorithms PDF eBook
Author Sukanta Nayak
Publisher Academic Press
Pages 323
Release 2020-08-25
Genre Technology & Engineering
ISBN 0128224924

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Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLAB© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice. - Presents optimization techniques clearly, including worked-out examples, from traditional to advanced - Maps out the relations between optimization and other mathematical topics and disciplines - Provides systematic coverage of algorithms to facilitate computer coding - Gives MATLAB© codes in relation to optimization techniques and their use in computer-aided design - Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks

Numerical Optimization in Engineering and Sciences

Numerical Optimization in Engineering and Sciences
Title Numerical Optimization in Engineering and Sciences PDF eBook
Author Debashis Dutta
Publisher Springer Nature
Pages 569
Release 2020-04-07
Genre Technology & Engineering
ISBN 981153215X

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This book presents select peer-reviewed papers presented at the International Conference on Numerical Optimization in Engineering and Sciences (NOIEAS) 2019. The book covers a wide variety of numerical optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, electrical, chemical, computer, and electronics engineering. The major focus is on innovative ideas, current methods and latest results involving advanced optimization techniques. The contents provide a good balance between numerical models and analytical results obtained for different engineering problems and challenges. This book will be useful for students, researchers, and professionals interested in engineering optimization techniques.

Numerical Methods and Optimization in Finance

Numerical Methods and Optimization in Finance
Title Numerical Methods and Optimization in Finance PDF eBook
Author Manfred Gilli
Publisher Academic Press
Pages 638
Release 2019-08-16
Genre Business & Economics
ISBN 0128150653

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Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance.