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Introduction to unconstrained optimi...

Mishra, Shashi Kant.

Introduction to unconstrained optimization with R

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to unconstrained optimization with Rby Shashi Kant Mishra, Bhagwat Ram.
Author:	Mishra, Shashi Kant.
other author:	Ram, Bhagwat.
Published:	Singapore :Springer Singapore :2019.
Description:	xvi, 304 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Constrained optimization.
Online resource:	https://doi.org/10.1007/978-981-15-0894-3
ISBN:	9789811508943$q(electronic bk.)

Introduction to unconstrained optimization with R
Mishra, Shashi Kant.

Introduction to unconstrained optimization with R[electronic resource] /by Shashi Kant Mishra, Bhagwat Ram. - Singapore :Springer Singapore :2019. - xvi, 304 p. :ill., digital ;24 cm.

1. Introduction -- 2. Mathematical Foundations -- 3. Basics of R -- 4. First Order and Second Order Necessary Conditions -- 5. One Dimensional Optimization Methods -- 6. Steepest Descent Method -- 7. Newton's Method -- 8. Conjugate Direction Methods -- 9. Quasi-Newton Methods.

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.

ISBN: 9789811508943$q(electronic bk.)

Standard No.: 10.1007/978-981-15-0894-3doiSubjects--Topical Terms:

455920
Constrained optimization.

LC Class. No.: QA323 / .M57 2019

Dewey Class. No.: 519.6

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100 1 $a Mishra, Shashi Kant. $3 274813
245 1 0 $a Introduction to unconstrained optimization with R $h [electronic resource] / $c by Shashi Kant Mishra, Bhagwat Ram.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xvi, 304 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1. Introduction -- 2. Mathematical Foundations -- 3. Basics of R -- 4. First Order and Second Order Necessary Conditions -- 5. One Dimensional Optimization Methods -- 6. Steepest Descent Method -- 7. Newton's Method -- 8. Conjugate Direction Methods -- 9. Quasi-Newton Methods.
520 $a 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.
650 0 $a Constrained optimization. $3 455920
650 0 $a R (Computer program language) $3 210846
650 1 4 $a Optimization. $3 274084
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 274020
700 1 $a Ram, Bhagwat. $3 856994
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-15-0894-3
950 $a Mathematics and Statistics (Springer-11649)