Just released:
Engineering Optimization: Applications,
Methods, and Analysis
R. Russell Rhinehart, 2018
John Wiley & Sons, ISBN-13: 978-1118936337, ISBN-10:1118936337,
776 pages.
An Application-Oriented Introduction to Essential Optimization Concepts
and Best Practices
The book provides a practically-focused introduction to modern
engineering optimization best practices, covering fundamental analytical and
numerical techniques throughout each stage of the optimization process.
Although essential
algorithms are explained in detail, the focus lies more in the human function:
how to create an appropriate objective function, choose decision variables,
identify and incorporate constraints, define convergence, and other critical
issues that define the success or failure of an optimization project.
Examples, exercises,
and homework throughout reinforce the author’s “do, not study” approach to
learning, underscoring the application-oriented discussion that provides a generic understanding of the optimization process that can be applied to
any field.
Providing excellent
reference for students or professionals, Engineering Optimization:
·
Describes and develops
a variety of algorithms, including gradient based (such as Newton’s, and
Levenberg-Marquardt), direct search (such as Hooke-Jeeves, Leapfrogging, and
Particle Swarm), along with surrogate functions for surface characterization
·
Provides guidance on
optimizer choice by application, and explains how to determine appropriate
optimizer parameter values
·
Details current best
practices for critical stages of specifying an optimization procedure,
including decision variables, defining constraints, and relationship modeling
Access to
software and open source Visual Basic macros for Excel is provided on the companion website, www.r3eda.com, along with
solutions to examples presented in the book.
Clear explanations,
explicit equation derivations, and practical examples make this book ideal for
use as part of a class or self-study, assuming a basic understanding of
statistics, calculus, computer programming, and engineering models. Anyone
seeking best practices for “making the best choices” will find value in this
introductory resource.
