Optimization theory : a concise introduction / Jiongmin Yong

By:

Yong, Jiongmin

Material type: Text

TextPublication details: Singapore World Scientific Publishing 2018Description: 223 pISBN:

9789813237643 (hardcover : alk. paper)

Subject(s):

DDC classification:

519.6 YON-J

LOC classification:

QA402.5 .Y66 2018

Contents:

Mathematical preparations -- Optimization problems and existence of optimal solutions -- Necessary and sufficient conditions of optimal solutions -- Problems with convexity and quasi-convexity conditions -- Linear programming.

Summary: "Mathematically, most of the interesting optimization problems can be formulated to optimize some objective function, subject to some equality and/or inequality constraints. This book introduces some classical and basic results of optimization theory, including nonlinear programming with Lagrange multiplier method, the Karush-Kuhn-Tucker method, Fritz John's method, problems with convex or quasi-convex constraints, and linear programming with geometric method and simplex method. A slim book such as this which touches on major aspects of optimization theory will be very much needed for most readers. We present nonlinear programming, convex programming, and linear programming in a self-contained manner. This book is for a one-semester course for upper level undergraduate students or first/second year graduate students. It should also be useful for researchers working on many interdisciplinary areas other than optimization"--

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Holdings
Item type	Current library	Collection	Shelving location	Call number	Status	Date due	Barcode	Item holds
Books	BITS Pilani Hyderabad	510	General Stack (For lending)	519.6 YON-J (Browse shelf(Opens below))	Available		38946

Total holds: 0

Mathematically, most of the interesting optimization problems can be formulated to optimize some objective function, subject to some equality and/or inequality constraints. This book introduces some classical and basic results of optimization theory, including nonlinear programming with Lagrange multiplier method, the Karush-Kuhn-Tucker method, Fritz John's method, problems with convex or quasi-convex constraints, and linear programming with geometric method and simplex method.A slim book such as this which touches on major aspects of optimization theory will be very much needed for most readers. We present nonlinear programming, convex programming, and linear programming in a self-contained manner. This book is for a one-semester course for upper level undergraduate students or first/second year graduate students. It should also be useful for researchers working on many interdisciplinary areas other than optimization.

Includes bibliographical references and index.

"Mathematically, most of the interesting optimization problems can be formulated to optimize some objective function, subject to some equality and/or inequality constraints. This book introduces some classical and basic results of optimization theory, including nonlinear programming with Lagrange multiplier method, the Karush-Kuhn-Tucker method, Fritz John's method, problems with convex or quasi-convex constraints, and linear programming with geometric method and simplex method. A slim book such as this which touches on major aspects of optimization theory will be very much needed for most readers. We present nonlinear programming, convex programming, and linear programming in a self-contained manner. This book is for a one-semester course for upper level undergraduate students or first/second year graduate students. It should also be useful for researchers working on many interdisciplinary areas other than optimization"--

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