SpringerLink
Log in

Basics of Optimization Theory

  • Textbook
  • © 2023

Overview

Authors:
  1. Arthur David Snider

    1. University of South Florida, Tampa, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Features innovative perspectives on the simplex algorithm and Krushal-Kuhn-Tucker-John conditions
  • Serves as a resource for readers to use the tools of optimization without needing to acquire expertise in the theory
  • Features plentiful resources that focus on rigorous definitions, proofs, and case studies

Part of the book series: Synthesis Lectures on Mathematics & Statistics (SLMS)

  • 1271 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 34.99
Price excludes VAT (Canada)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 44.99
Price excludes VAT (Canada)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

This book presents a short introduction to the main tools of optimization methodology including linear programming, steepest descent, conjugate gradients, and the Karush-Kuhn-Tucker-John conditions. Each topic is developed in terms of a specific physical model, so that the strategy behind every step is motivated by a logical, concrete, easily visualized objective. A quick perusal of the Fibonacci search algorithm provides a simple and tantalizing first encounter with optimization theory, and a review of the max-min exposition of one-dimensional calculus prepares readers for the more sophisticated topics found later in the book. Notable features are the innovative perspectives on the simplex algorithm and Karush-Kuhn-Tucker-John conditions as well as a wealth of helpful diagrams. The author provides pointers to references for readers who would like to learn more about rigorous definitions, proofs, elegant reformulations and extensions, and case studies. However, the book is sufficiently self-contained to serve as a reliable resource for readers who wish to exploit commercially available optimization software without investing the time to develop expertise in its aspects.

This book also:
  • Features innovative perspectives on the simplex algorithm and Krushal-Kuhn-Tucker-John conditions
  • Serves as a resource for readers to use the tools of optimization without needing to acquire expertise in the theory
  • Features  plentiful resources that focus on rigorous definitions, proofs, and case studies




Keywords

Table of contents (6 chapters)

  1. Front Matter

    Pages i-viii
    Download chapter PDF

  2. Fibonacci Search

    • Arthur David Snider
    Pages 1-11

  3. Linear Programming

    • Arthur David Snider
    Pages 13-102

  4. Nonlinear Programming in One Dimension

    • Arthur David Snider
    Pages 103-108

  5. Nonlinear Multidimensional Optimization

    • Arthur David Snider
    Pages 109-128

  6. Constrained Optimization

    • Arthur David Snider
    Pages 129-139

  7. What’s Left?

    • Arthur David Snider
    Pages 141-143
Back to top

Authors and Affiliations

  • University of South Florida, Tampa, USA

    Arthur David Snider

About the author

Arthur David Snider, PhD., is a Professor Emeritus in the Departments of Mathematics, Physics, and Electrical Engineering at the University of South Florida. He has 50+ years of experience in modeling physical systems in the areas of heat transfer, electromagnetics, microwave circuits, and orbital mechanics, as well as the mathematical areas of numerical analysis, signal processing, differential equations, and optimization.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation