Introduction to nonlinear optimization: theory, algorithms, and applications with python and MATLAB

By:

Beck, Amir

Series: MOS-SIAM Series on OptimizationPublication details: Philadelphia: SIAM- Society for Industrial and Applied Mathematics & Mathematical Optimization Society, 2023Edition: 2nd edDescription: xii, 351p.: col.ill.: pbk.: 25cmISBN:

9781611977615

Subject(s):

DDC classification:

515.642 BEC

Summary: Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author's objective is to provide the foundations of theory and algorithms of nonlinear optimization, as well as to present a variety of applications from diverse areas of applied sciences. Introduction to Nonlinear Optimization gradually yet rigorously builds, connections between theory, algorithms, applications, and actual implementation; contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares; includes a wide array of applications such as circle fitting, Chebyshev center, the Fermat-Weber problem, denoising, clustering, total least squares, and orthogonal regression; studies applications both theoretically and algorithmically, illustrating concepts such as duality. Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used. More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples. https://epubs.siam.org/doi/book/10.1137/1.9781611977622

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	IIT Gandhinagar	General	515.642 BEC (Browse shelf(Opens below))	1	Available		033626

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Previous	515.64 SAS Nonlinear systems : analysis, stability, and control	515.64 SAS Nonlinear systems : analysis, stability, and control	515.64 WEI Calculus of variations : with applications to physics and engineering	515.642 BEC Introduction to nonlinear optimization: theory, algorithms, and applications with python and MATLAB	515.642 GLO Exact and approximate controllability for distributed parameter systems: a numerical approach, Vol. 117	515.642 JUR Optimal control and geometry: integrable systems	515.7 ARO J-contractive matrix valued functions and related topics, Vol. 116	Next

Includes Bibliographic Notes, Bibliography and Index

Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author's objective is to provide the foundations of theory and algorithms of nonlinear optimization, as well as to present a variety of applications from diverse areas of applied sciences.

Introduction to Nonlinear Optimization

gradually yet rigorously builds, connections between theory, algorithms, applications, and actual implementation;

contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares;

includes a wide array of applications such as circle fitting, Chebyshev center, the Fermat-Weber problem, denoising, clustering, total least squares, and orthogonal regression;

studies applications both theoretically and algorithmically, illustrating concepts such as duality.

Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used.

More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples.

https://epubs.siam.org/doi/book/10.1137/1.9781611977622

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