Claim your complimentary eBook worth $106 for free today, before the offer expires!
Accessible introductory textbook on optimization theory and methods, with an emphasis on engineering design, featuring MATLAB® exercises and worked examples
Fully updated to reflect modern developments in the field, the Fifth Edition of An Introduction to Optimization fills the need for an accessible, yet rigorous, introduction to optimization theory and methods, featuring innovative coverage and a straightforward approach. The book begins with a review of basic definitions and notations while also providing the related fundamental background of linear algebra, geometry, and calculus.
With this foundation, the authors explore the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization, and applications of optimization in machine learning.
Numerous diagrams and figures found throughout the book complement the written presentation of key concepts, and each chapter is followed by MATLAB® exercises and practice problems that reinforce the discussed theory and algorithms.
The Fifth Edition features a new chapter on Lagrangian (nonlinear) duality, expanded coverage on matrix games, projected gradient algorithms, machine learning, and numerous new exercises at the end of each chapter.
An Introduction to Optimization includes information on:
The mathematical definitions, notations, and relations from linear algebra, geometry, and calculus used in optimization Optimization algorithms, covering one-dimensional search, randomized search, and gradient, Newton, conjugate direction, and quasi-Newton methods Linear programming methods, covering the simplex algorithm, interior point methods, and duality Nonlinear constrained optimization, covering theory and algorithms, convex optimization, and Lagrangian duality Applications of optimization in machine learning, including neural network training, classification, stochastic gradient descent, linear regression, logistic regression, support vector machines, and clustering.
An Introduction to Optimization is an ideal textbook for a one- or two-semester senior undergraduate or beginning graduate course in optimization theory and methods. The text is also of value for researchers and professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.
The below offers are also available for free in exchange for your (work) email:
Generative AI For Dummies ($18 Value) FREE - Expires 11/26
An Introduction to Optimization[*], 5th Edition ($106 Value) FREE - Expires 11/26
VideoProc Converter for AI ($78.90 Value) FREE - Expires 11/27
The AI Value Playbook ($35.99 Value) Free Limited Time Offer - Expires 11/27
WinX DVD Ripper Platinum V8.22.2 ($65.95 FREE - Expires 11/30
Python Notes for Professionals - Featured Free content
Learn Linux in 5 Days - Featured Free content
Quick Reference Guide for Cybersecurity - Featured Free content
How to get it
Please ensure you read the terms and conditions to claim this offer. Complete and verifiable information is required in order to receive this free offer. If you have previously made use of these free offers, you will not need to re-register. While supplies last!
An Introduction to Optimization - 5th Edition (worth $106) - Free eBook
Offered by Wiley, view other free resources | Limited time offer
We post these because we earn commission on each lead so as not to rely solely on advertising, which many of our readers block. It all helps toward paying staff reporters, servers and hosting costs.
Other ways to support Neowin
The above not doing it for you, but still want to help? Check out the links below.
Check out our partner software in the Neowin Store Buy a T-shirt at Neowin's Threadsquad Subscribe to Neowin - for $14 a year, or $28 a year for an ad-free experience
Disclosure: An account at Neowin Deals is required to participate in any deals powered by our affiliate, StackCommerce. For a full description of StackCommerce's privacy guidelines, go here. Neowin benefits from shared revenue of each sale made through our branded deals site.