Author : Mohamed Bakr
Publisher : IET
Page : 325 pages
File Size : 20,87 MB
Release : 2013-09-09
Category : Computers
ISBN : 1849195439
Nonlinear Optimization in Electrical Engineering with Applications in MATLAB® provides an introductory course on nonlinear optimization in electrical engineering, with a focus on applications such as the design of electric, microwave, and photonic circuits, wireless communications, and digital filter design.
Author : Shashi Kant Mishra
Publisher : Springer Nature
Page : 309 pages
File Size : 20,60 MB
Release : 2019-12-17
Category : Mathematics
ISBN : 9811508941
This book discusses unconstrained optimization with R—a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.
Author : Mohammad Fathi
Publisher : Springer
Page : 177 pages
File Size : 14,66 MB
Release : 2019-03-01
Category : Technology & Engineering
ISBN : 3030053091
This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering. Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.
Author : Amir Beck
Publisher : SIAM
Page : 286 pages
File Size : 15,6 MB
Release : 2014-10-27
Category : Mathematics
ISBN : 1611973651
This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.
Author : Amir Beck
Publisher : SIAM
Page : 286 pages
File Size : 21,40 MB
Release : 2014-10-27
Category : Mathematics
ISBN : 1611973643
This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.
Author : Achille Messac
Publisher : Cambridge University Press
Page : 503 pages
File Size : 40,76 MB
Release : 2015-03-19
Category : Computers
ISBN : 1107109183
This textbook is designed for students and industry practitioners for a first course in optimization integrating MATLAB® software.
Author : Michel C. Delfour
Publisher : SIAM
Page : 446 pages
File Size : 47,96 MB
Release : 2019-12-19
Category : Mathematics
ISBN : 1611975964
This second edition provides an enhanced exposition of the long-overlooked Hadamard semidifferential calculus, first introduced in the 1920s by mathematicians Jacques Hadamard and Maurice René Fréchet. Hadamard semidifferential calculus is possibly the largest family of nondifferentiable functions that retains all the features of classical differential calculus, including the chain rule, making it a natural framework for initiating a large audience of undergraduates and non-mathematicians into the world of nondifferentiable optimization. Introduction to Optimization and Hadamard Semidifferential Calculus, Second Edition builds upon its prior editions foundations in Hadamard semidifferential calculus, showcasing new material linked to convex analysis and nonsmooth optimization. It presents a modern treatment of optimization and Hadamard semidifferential calculus while remaining at a level that is accessible to undergraduate students, and challenges students with exercises related to problems in such fields as engineering, mechanics, medicine, physics, and economics. Answers are supplied in Appendix B. Students of mathematics, physics, engineering, economics, and other disciplines that demand a basic knowledge of mathematical analysis and linear algebra will find this a fitting primary or companion resource for their studies. This textbook has been designed and tested for a one-term course at the undergraduate level. In its full version, it is appropriate for a first-year graduate course and as a reference.
Author : Marco C. Campi
Publisher : SIAM
Page : 121 pages
File Size : 25,62 MB
Release : 2018-11-15
Category : Mathematics
ISBN : 1611975433
This book is about making decisions driven by experience. In this context, a scenario is an observation that comes from the environment, and scenario optimization refers to optimizing decisions over a set of available scenarios. Scenario optimization can be applied across a variety of fields, including machine learning, quantitative finance, control, and identification. This concise, practical book provides readers with an easy access point to make the scenario approach understandable to nonexperts, and offers an overview of various decision frameworks in which the method can be used. It contains numerous examples and diverse applications from a broad range of domains, including systems theory, control, biomedical engineering, economics, and finance. Practitioners can find "easy-to-use recipes," while theoreticians will benefit from a rigorous treatment of the theoretical foundations of the method, making it an excellent starting point for scientists interested in doing research in this field. Introduction to the Scenario Approach will appeal to scientists working in optimization, practitioners working in myriad fields involving decision-making, and anyone interested in data-driven decision-making.
Author : Tamas Terlaky
Publisher : SIAM
Page : 730 pages
File Size : 26,75 MB
Release : 2017-04-26
Category : Mathematics
ISBN : 1611974674
Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.
Author : Sergey E. Lyshevski
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 21,63 MB
Release : 2003-06-16
Category : Computers
ISBN : 0471462004
Master MATLAB(r) step-by-step The MATLAB-- "MATrix LABoratory"--computational environment offers a rich set of capabilities to efficiently solve a variety of complex analysis, simulation, and optimization problems. Flexible, powerful, and relatively easy to use, the MATLAB environment has become a standard cost-effective tool within the engineering, science, and technology communities. Excellent as a self-teaching guide for professionals as well as a textbook for students, Engineering and Scientific Computations Using MATLAB helps you fully understand the MATLAB environment, build your skills, and apply its features to a wide range of applications. Going beyond traditional MATLAB user manuals and college texts, Engineering and Scientific Computations Using MATLAB guides you through the most important aspects and basics of MATLAB programming and problem-solving from fundamentals to practice. Augmenting its discussion with a wealth of practical worked-out examples and qualitative illustrations, this book demonstrates MATLAB's capabilities and offers step-by-step instructions on how to apply the theory to a practical real-world problem. In particular, the book features: * Coverage of a variety of complex physical and engineering systems described by nonlinear differential equations * Detailed application of MATLAB to electromechanical systems MATLAB files, scripts, and statements, as well as SIMULINK models which can be easily modified for application-specific problems encountered in practice Readable, user-friendly, and comprehensive in scope this is a welcome introduction to MATLAB for those new to the program and an ideal companion for engineers seeking in-depth mastery of the high-performance MATLAB environment.
