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Books > Science & Mathematics > Mathematics > Optimization
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Engineering Optimization - Applications, Methods and Analysis (Hardcover)
Loot Price: R2,956
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Engineering Optimization - Applications, Methods and Analysis (Hardcover)
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An Application-Oriented Introduction to Essential Optimization
Concepts and Best Practices Optimization is an inherent human
tendency that gained new life after the advent of calculus; now, as
the world grows increasingly reliant on complex systems,
optimization has become both more important and more challenging
than ever before. Engineering Optimization 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 deep, 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 Provides
access to software and Visual Basic macros for Excel on the
companion website, 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.
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