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Linear Optimization [electronic resource] : The Simplex Workbook / by Glenn Hurlbert.

By: Hurlbert, Glenn [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Undergraduate Texts in Mathematics: Publisher: New York, NY : Springer New York, 2010Description: online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780387791487.Subject(s): Mathematics | Algorithms | Combinatorics | Mathematical optimization | Operations research | Mathematics | Operations Research, Mathematical Programming | Optimization | Combinatorics | AlgorithmsDDC classification: 519.6 Online resources: Click here to access online
Contents:
The Simplex Algorithm -- Geometry -- The Duality Theorem -- Matrix Environment -- General Form -- Unsolvable Systems -- Geometry Revisited -- Game Theory -- Network Environment -- Combinatorics -- Economics -- Integer Optimization.
In: Springer eBooksSummary: This undergraduate textbook is written for a junior/senior level course on linear optimization. Unlike other texts, the treatment allows the use of the "modified Moore method" approach by working examples and proof opportunities into the text in order to encourage students to develop some of the content through their own experiments and arguments while reading the text. Additionally, the focus is on the mathematics underlying the ideas of optimizing linear functions under linear constraints and the algorithms used to solve them. In particular, the author uses the Simplex Algorithm to motivate these concepts. The text progresses at a gentle and inviting pace. The presentation is driven by numerous examples and illustrations. Ample exercises are provided at the end of each chapter for mastering the material. Opportunities for integrating Maple (or similar) software are included in the book. The author’s own WebSim software can be freely downloaded from his website for pedagogical use. The teacher's version of the text contains solutions embedded within the text, rather than in an appendix. It also has extra material and suggestions for the teacher’s benefit. Junior/senior level undergraduate students will benefit from the book, as will beginning graduate students. Future secondary school mathematics teachers will also find this book useful. Arizona State University Professor Glenn H. Hurlbert has published nearly 50 articles in graph theory, combinatorics, and optimization, and has been the recipient of numerous teaching and mentoring awards from ASU, the ASU Parents Association, the School of Mathematical and Statistical Sciences, and the Mathematical Association of America.
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The Simplex Algorithm -- Geometry -- The Duality Theorem -- Matrix Environment -- General Form -- Unsolvable Systems -- Geometry Revisited -- Game Theory -- Network Environment -- Combinatorics -- Economics -- Integer Optimization.

This undergraduate textbook is written for a junior/senior level course on linear optimization. Unlike other texts, the treatment allows the use of the "modified Moore method" approach by working examples and proof opportunities into the text in order to encourage students to develop some of the content through their own experiments and arguments while reading the text. Additionally, the focus is on the mathematics underlying the ideas of optimizing linear functions under linear constraints and the algorithms used to solve them. In particular, the author uses the Simplex Algorithm to motivate these concepts. The text progresses at a gentle and inviting pace. The presentation is driven by numerous examples and illustrations. Ample exercises are provided at the end of each chapter for mastering the material. Opportunities for integrating Maple (or similar) software are included in the book. The author’s own WebSim software can be freely downloaded from his website for pedagogical use. The teacher's version of the text contains solutions embedded within the text, rather than in an appendix. It also has extra material and suggestions for the teacher’s benefit. Junior/senior level undergraduate students will benefit from the book, as will beginning graduate students. Future secondary school mathematics teachers will also find this book useful. Arizona State University Professor Glenn H. Hurlbert has published nearly 50 articles in graph theory, combinatorics, and optimization, and has been the recipient of numerous teaching and mentoring awards from ASU, the ASU Parents Association, the School of Mathematical and Statistical Sciences, and the Mathematical Association of America.

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