For students in industrial and systems engineering (ISE) and
operations research (OR) to understand optimization at an advanced
level, they must first grasp the analysis of algorithms,
computational complexity, and other concepts and modern
developments in numerical methods. Satisfying this prerequisite,
Numerical Methods and Optimization: An Introduction combines the
materials from introductory numerical methods and introductory
optimization courses into a single text. This classroom-tested
approach enriches a standard numerical methods syllabus with
optional chapters on numerical optimization and provides a valuable
numerical methods background for students taking an introductory OR
or optimization course.
The first part of the text introduces the necessary mathematical
background, the digital representation of numbers, and different
types of errors associated with numerical methods. The second part
explains how to solve typical problems using numerical methods.
Focusing on optimization methods, the final part presents basic
theory and algorithms for linear and nonlinear optimization.
The book assumes minimal prior knowledge of the topics. Taking a
rigorous yet accessible approach to the material, it includes some
mathematical proofs as samples of rigorous analysis but in most
cases, uses only examples to illustrate the concepts. While the
authors provide a MATLAB(r) guide and code available for download,
the book can be used with other software packages.
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