9781470441142-1470441144-Mathematics of Optimization: How to Do Things Faster (Pure and Applied Undergraduate Texts) (Pure and Applied Undergraduate Texts, 30)

Mathematics of Optimization: How to Do Things Faster (Pure and Applied Undergraduate Texts) (Pure and Applied Undergraduate Texts, 30)

ISBN-13: 9781470441142
ISBN-10: 1470441144
Author: Steven J. Miller
Publication date: 2017
Publisher: American Mathematical Society
Format: Hardcover 327 pages
Category: Mathematics
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Book details

ISBN-13: 9781470441142
ISBN-10: 1470441144
Author: Steven J. Miller
Publication date: 2017
Publisher: American Mathematical Society
Format: Hardcover 327 pages
Category: Mathematics

Summary

Mathematics of Optimization: How to Do Things Faster (Pure and Applied Undergraduate Texts) (Pure and Applied Undergraduate Texts, 30) (ISBN-13: 9781470441142 and ISBN-10: 1470441144), written by authors Steven J. Miller, was published by American Mathematical Society in 2017. With an overall rating of 3.9 stars, it's a notable title among other Mathematics books. You can easily purchase or rent Mathematics of Optimization: How to Do Things Faster (Pure and Applied Undergraduate Texts) (Pure and Applied Undergraduate Texts, 30) (Hardcover) from BooksRun, along with many other new and used Mathematics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $8.05.

Description

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.

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