Linear Programming Using MATLAB®
Nikolaos Ploskas, Nikolaos SamarasThis 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.Категории:
Год:
2017
Издание:
1
Издательство:
Springer International Publishing
Язык:
english
Страницы:
642
ISBN 10:
3319659197
ISBN 13:
9783319659190
Серия:
Springer Optimization and Its Applications 127
Файл:
PDF, 7.75 MB
IPFS:
,
english, 2017
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