書目名稱 | Linear Programming Using MATLAB? |
編輯 | Nikolaos Ploskas,Nikolaos Samaras |
視頻video | http://file.papertrans.cn/587/586399/586399.mp4 |
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 |
叢書名稱 | Springer Optimization and Its Applications |
圖書封面 |  |
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 |
關鍵詞 | 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 |