Introduction to Nonlinear Optimization

Introduction to Nonlinear Optimization

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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 optimizationA—theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problemsA—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 booksA—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 FermatA–Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLABA’ toolbox CVX and a package of m-files that is posted on the bookA’s web site.Matrix analysis and applied linear algebra. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2000. With 1 CD-ROM (Windows, Macintosh and UNIX) and a solutions manual (iv+171 pp.). [25] J. J. MorAc. Generalizationsanbsp;...

Title:Introduction to Nonlinear Optimization
Author:Amir Beck
Publisher:SIAM - 2014-10-27


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