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Numerical Methods and Optimization
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Numerical Methods and Optimization : An Introduction

Book Details

Format Hardback or Cased Book
ISBN-10 1466577770
ISBN-13 9781466577770
Publisher Taylor & Francis Inc
Imprint CRC Press Inc
Country of Manufacture US
Country of Publication GB
Publication Date Mar 11th, 2014
Print length 414 Pages
Weight 806 grams
Dimensions 24.00 x 16.60 x 2.70 cms
Product Classification: Mathematical theory of computation
Ksh 17,100.00
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This book 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 optimization or operations research course. The book includes some mathematical proofs as samples of rigorous analysis but in most cases, uses only examples to illustrate the concepts. A MATLAB® guide and code are available for download.

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® guide and code available for download, the book can be used with other software packages.


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