| 書目名稱 | Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice | | 編輯 | Daniel Bienstock | | 視頻video | http://file.papertrans.cn/753/752377/752377.mp4 | | 叢書名稱 | International Series in Operations Research & Management Science | | 圖書封面 |  | | 描述 | .Potential Function Methods For Approximately Solving Linear Programming Problems. breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments. | | 出版日期 | Book 2002 | | 關(guān)鍵詞 | algorithms; design; linear optimization; mathematical programming; optimization; programming | | 版次 | 1 | | doi | https://doi.org/10.1007/b115460 | | isbn_softcover | 978-1-4757-7672-0 | | isbn_ebook | 978-0-306-47626-6Series ISSN 0884-8289 Series E-ISSN 2214-7934 | | issn_series | 0884-8289 | | copyright | Springer Science+Business Media New York 2002 |
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