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Nonlinear Optimization

  • Francisco J. Aragón
  • Miguel A. Goberna
  • Marco A. López
  • Margarita M.L. Rodríguez

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
    Pages 1-51
  3. Analytical Optimization

    1. Front Matter
      Pages 53-53
    2. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
      Pages 55-89
    3. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
      Pages 91-116
    4. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
      Pages 117-180
  4. Numerical Optimization

    1. Front Matter
      Pages 181-181
    2. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
      Pages 183-252
    3. Francisco J. Aragón, Miguel A. Goberna, Marco A. López, Margarita M. L. Rodríguez
      Pages 253-309
  5. Back Matter
    Pages 311-350

About this book

Introduction

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.

Keywords

convexity coercivity linear regression Jensen's inequalities polynomial regression Lagrange duality Nelder and Mead method Fermat-Steiner problem Quasi-Newton methods optimization problems unconstrained optimization geometric optimizqtion quadratic optimiztion wolfe duality optimization algorithms line search methods gradient methods derivative-free optimization methods constrained optimization

Authors and affiliations

  • Francisco J. Aragón
    • 1
  • Miguel A. Goberna
    • 2
  • Marco A. López
    • 3
  • Margarita M.L. Rodríguez
    • 4
  1. 1.Department of MathematicsUniversity of AlicanteAlicanteSpain
  2. 2.Department of MathematicsUniversity of AlicanteAlicanteSpain
  3. 3.Department of MathematicsUniversity of AlicanteAlicanteSpain
  4. 4.Department of MathematicsUniversity of AlicanteAlicanteSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-11184-7
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-11183-0
  • Online ISBN 978-3-030-11184-7
  • Series Print ISSN 1867-5506
  • Series Online ISSN 1867-5514
  • Buy this book on publisher's site