Linear and non-linear optimization

By:

Griva, Igor

Contributor(s):

Material type: Text

TextLanguage: Eng Publication details: Hyderabad: University Press (India) Pvt. Ltd, 2018Edition: 2nd edDescription: xxii, 742p. : ill. ; 25cmISBN:

9789386235374

Subject(s):

DDC classification:

519.72 GRI 23rd

Summary: This book introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. This book is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate and graduate students. It is also appropriate as a tutorial for researchers and practitioners who need to understand the modern algorithms of linear and nonlinear optimization to apply them to problems in science and engineering. Also includes bibliographical references and index.

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Books	Vigyanpuri Campus	519.72 GRI (Browse shelf(Opens below))	Available	006581
Books	Vigyanpuri Campus	519.72 GRI (Browse shelf(Opens below))	Available	006587
Books	Vigyanpuri Campus	519.72 GRI (Browse shelf(Opens below))	Available	006585
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Books	Vigyanpuri Campus	519.72 GRI (Browse shelf(Opens below))	Available	006582
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Books	Vigyanpuri Campus	519.72 GRI (Browse shelf(Opens below))	Available	006579
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This book introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines.

This book is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate and graduate students. It is also appropriate as a tutorial for researchers and practitioners who need to understand the modern algorithms of linear and nonlinear optimization to apply them to problems in science and engineering.

Also includes bibliographical references and index.

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