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Nonlinear optimization

Aragon, Francisco J.

Nonlinear optimization

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nonlinear optimizationby Francisco J. Aragon ... [et al.].
其他作者:	Aragon, Francisco J.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xiv, 350 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Mathematical optimization.
電子資源:	https://doi.org/10.1007/978-3-030-11184-7
ISBN:	9783030111847$q(electronic bk.)

Nonlinear optimization
Nonlinear optimization[electronic resource] /by Francisco J. Aragon ... [et al.]. - Cham :Springer International Publishing :2019. - xiv, 350 p. :ill., digital ;24 cm. - Springer undergraduate texts in mathematics and technology,1867-5506. - Springer undergraduate texts in mathematics and technology..

1. Preliminaries -- Part I. Analytical Optimization -- 2. Convexity -- 3. Unconstrained Optimization -- 4. Convex Optimization -- Part II. Numerical Optimization -- 5. Unconstrained Optimization Algorithms -- 6. Constrained Optimization -- Solutions to selected exercises -- References -- Index.

This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.

ISBN: 9783030111847$q(electronic bk.)

Standard No.: 10.1007/978-3-030-11184-7doiSubjects--Topical Terms:

183292
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Nonlinear optimization
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505 0 $a 1. Preliminaries -- Part I. Analytical Optimization -- 2. Convexity -- 3. Unconstrained Optimization -- 4. Convex Optimization -- Part II. Numerical Optimization -- 5. Unconstrained Optimization Algorithms -- 6. Constrained Optimization -- Solutions to selected exercises -- References -- Index.
520 $a This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.
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