Linear Programming Using MATLAB® (Springer Optimization and Its Applications). Questo articolo non è disponibile.
Lingua: inglese
Editore: Springer, 2018
Serie: Libro 117 di 176 - Springer Optimization and Its Applications
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reprint edition. 664 pages. 9.25x6.10x1.42 inches. In Stock.
Codice articolo 3319881310
- Titolo
- Linear Programming Using MATLAB® (Springer Optimization and Its Applications)
- Autore
- Ploskas, Nikolaos
- Editore
- Springer
- Anno di pubblicazione
- 2018
- Condizione
- Brand New
- Rilegatura
- Paperback
- Lingua
- inglese
- ISBN 10
- 3319881310
- ISBN 13
- 9783319881317
- Peso dell'articolo
- 0,96 chilogrammi
- Serie
- Libro 117 di 176: Springer Optimization and Its Applications
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."Riassunto" può appartenere a un’altra edizione di questo titolo.
Dalla quarta di copertina
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.
"Descrizione articolo" può appartenere a un’altra edizione di questo titolo.