| 000 | 01935nam a22002895i 4500 | ||
|---|---|---|---|
| 001 | 40243 | ||
| 003 | 0000000000 | ||
| 005 | 20240308015819.0 | ||
| 008 | 170822s2017 nyu s 000 0 eng | ||
| 010 | _a 2017953041 | ||
| 020 | _a9783319659176 | ||
| 035 | _a19961627 | ||
| 040 |
_aDLC _beng _erda _cDLC |
||
| 042 | _apcc | ||
| 245 | 0 | 0 |
_aLinear programming using Matlab / _cNikolaos Ploskas and Nikolaos Samaras. |
| 263 | _a1710 | ||
| 264 | 1 |
_aNew York, NY : _bCham, _c2017. |
|
| 300 | _apages cm. | ||
| 336 |
_atext _2rdacontent |
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| 337 |
_acomputer _2rdamedia |
||
| 338 |
_aonline resource _2rdacarrier |
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| 520 | _aThis 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. | ||
| 650 | 7 |
_a Linear programming. _2sears |
|
| 650 | 7 |
_aComputer science -- Mathematics. _2sears |
|
| 650 | 7 |
_aMathematics. _2sears |
|
| 856 | _uhttps://drive.google.com/file/d/1Iq4Bq9lLXpBY-wx1rzxlh9-DV3Qdh224/view?usp=sharing | ||
| 999 |
_c26483 _d26483 |
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