Mathematics of Optimization: How to Do Things Faster

Author:   Steven J. Miller
Publisher:   American Mathematical Society
ISBN:  

9781470441142


Pages:   327
Publication Date:   30 January 2018
Format:   Hardback
Availability:   In Print   Availability explained
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Mathematics of Optimization: How to Do Things Faster


Overview

Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the ""why"" and the ""how"" in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings.

Full Product Details

Author:   Steven J. Miller
Publisher:   American Mathematical Society
Imprint:   American Mathematical Society
Weight:   0.760kg
ISBN:  

9781470441142


ISBN 10:   1470441144
Pages:   327
Publication Date:   30 January 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Classical algorithms: Efficient multiplication, I Efficient multiplication, II Introduction to linear programming: Introduction to linear programming The canonical linear programming problem Symmetries and dualities Basic feasible and basic optimal solutions The simplex method Advanced linear programming: Integer programming Integer optimization Multi-objective and quadratic programming The traveling salesman problem Introduction to stochastic linear programming Fixed point theorems: Introduction to fixed point theorems Contraction maps Sperner's lemma Brouwer's fixed point theorem Advanced topics: Gale-Shapley algorithm Interpolating functions The four color problem The Kepler conjecture Index Bibliography.

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Author Information

Steven J. Miller, Williams College, Williamstown, MA.

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Latest Reading Guide

NOV RG 20252

 

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