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Understanding and using linear programming

By: Contributor(s): Material type: TextTextPublication details: New York Springer 2007Description: viii, 222pISBN:
  • 9783540306979 (pbk)
Subject(s): DDC classification:
  • 519.72  MAT
Summary: This is an introductory textbook of linear programming, written mainly for students of computer science and mathematics. Our guiding phrase is, "what every theoretical computer scientist should know about linear programming". The book is relatively concise, in order to allow the reader to focus on the basic ideas. For a number of topics commonly appearing in thicker books on the subject, we were seriously tempted to add them to the main text, but we decided to present them only very brie?y in a separate glossary. At the same time, we aim at covering the main results with complete proofs and in su?cient detail, in a way ready for presentation in class. One of the main focuses is applications of linear programming, both in practice and in theory. Linear programming has become an extremely ?- ible tool in theoretical computer science and in mathematics. While many of the ?nest modern applications are much too complicated to be included in an introductory text, we hope to communicate some of the ?avor (and excitement) of such applications on simpler examples.
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Item type Current library Collection Call number Status Date due Barcode
Book Book Plaksha University Library Mathematics 519.72 MAT (Browse shelf(Opens below)) Available 004643
Book Book Plaksha University Library Mathematics 519.72 MAT (Browse shelf(Opens below)) Available 004644
Book Book Plaksha University Library Mathematics 519.72 MAT (Browse shelf(Opens below)) Available 004645
Book Book Plaksha University Library Mathematics 519.72 MAT (Browse shelf(Opens below)) Available 004646

https://link.springer.com/book/10.1007/978-3-540-30717-4#about-this-book

This is an introductory textbook of linear programming, written mainly for students of computer science and mathematics. Our guiding phrase is, "what every theoretical computer scientist should know about linear programming". The book is relatively concise, in order to allow the reader to focus on the basic ideas. For a number of topics commonly appearing in thicker books on the subject, we were seriously tempted to add them to the main text, but we decided to present them only very brie?y in a separate glossary. At the same time, we aim at covering the main results with complete proofs and in su?cient detail, in a way ready for presentation in class. One of the main focuses is applications of linear programming, both in practice and in theory. Linear programming has become an extremely ?- ible tool in theoretical computer science and in mathematics. While many of the ?nest modern applications are much too complicated to be included in an introductory text, we hope to communicate some of the ?avor (and excitement) of such applications on simpler examples.

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