| 书目名称 | Linear Programming Using MATLAB® |
| 编辑 | Nikolaos Ploskas,Nikolaos Samaras |
| 视频video | |
| 概述 | Methodically presents all components of the simplex-type methods?.Enables readers to experiment with MATLAB® codes that are able to solve large-scale benchmark linear programs?.Contains 11 presolve te |
| 丛书名称 | Springer Optimization and Its Applications |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2017 |
| 关键词 | MATLAB linear programming; linear programming algorithms; parametric programming; scaling techniques; se |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-65919-0 |
| isbn_softcover | 978-3-319-88131-7 |
| isbn_ebook | 978-3-319-65919-0Series ISSN 1931-6828 Series E-ISSN 1931-6836 |
| issn_series | 1931-6828 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 16:12:25
