Linear Programming Using MATLAB®

Nonfiction, Science & Nature, Mathematics, Applied, Computers, Application Software
Cover of the book Linear Programming Using MATLAB® by Nikolaos Ploskas, Nikolaos Samaras, Springer International Publishing
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Author: Nikolaos Ploskas, Nikolaos Samaras ISBN: 9783319659190
Publisher: Springer International Publishing Publication: October 28, 2017
Imprint: Springer Language: English
Author: Nikolaos Ploskas, Nikolaos Samaras
ISBN: 9783319659190
Publisher: Springer International Publishing
Publication: October 28, 2017
Imprint: Springer
Language: English

This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book  are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms.

As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus.  The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book  are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms.

As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus.  The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.

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