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 Intro
"The book is in most parts very well developed and is served by nice illustrations, a fluid style of writing, and a layout that makes it easy to read. … [it will] serve well its purpose of bridging the gap between numerical analysis, operations research, and mathematical optimization for undergraduate students in the applied sciences."—Mathematical Reviews, August 2014"If you are looking for an enjoyable and useful introduction to the basic topics of numerical methods and optimization, this is the right text to read. The authors are not only experienced lecturers but also active researchers in this area. They present the basic topics of numerical methods and optimization in an easy-to-follow, yet rigorous manner. In particular, they gently introduce some important topics, such as computational complexity, which are usually unavailable in textbooks on optimization for engineers. The authors occasionally turn to mathematical humor (such as ‘There are 10 types of people—those who understand binary, and those who don't’) to illustrate some material in the text. This informal contact with the reader exemplifies the engaging style of exposition characteristic of this excellent book."—Oleg Burdakov, Linkoeping University, Sweden
Innehållsförteckning
Basics: Preliminaries. Numbers and Errors. Numerical Methods for Standard Problems: Elements of Numerical Linear Algebra. Solving Equations. Polynomial Interpolation. Numerical Integration. Numerical Solution of Differential Equations. Introduction to Optimization: Basic Concepts. Complexity Issues. Introduction to Linear Programming. The Simplex Method for Linear Programming. Duality and Sensitivity Analysis in Linear Programming. Unconstrained Optimization. Constrained Optimization. Notes and References. Bibliography. Index.