Linear programming using Matlab / Nikolaos Ploskas and Nikolaos Samaras.
Material type: TextPublisher: New York, NY : Cham, 2017Description: pages cmContent type:- text
- computer
- online resource
- 9783319659176
Item type | Current library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|
E-Resources | Main Library E-Resources | 519.6 P729 (Browse shelf(Opens below)) | Available | E002728 |
Browsing Main Library shelves, Shelving location: E-Resources Close shelf browser (Hides shelf browser)
519.57 D281 Design and analysis of experiments / | 519.6 N756 Numerical optimization | 519.6 Op61 Operations Research, Engineering, and Cyber Security : Trends in Applied Mathematics and Technology / | 519.6 P729 Linear programming using Matlab / | 519.7/03 Ex96 Extensions of dynamic programming for combinatorial optimization and data mining / | 519.7/2 P192 Linear programming and resource allocation modeling / | 519.7/2 R221 Optimization in operations research / |
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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