Interior point algorithms : theory and analysis
著者
書誌事項
Interior point algorithms : theory and analysis
Wiley, c1997
- タイトル別名
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Wiley-Interscience series in discrete mathematics and optimization
A Wiley-Interscience Publication
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注記
"This book has been electronically reproduced from digital information stored at John Wiley & Sons, Inc. ... The content of this book is identical to previous printings."--T.p. verso
Originally published in the series: Wiley-Interscience series in discrete mathematics and optimization
"A Wiley-Interscience Publication"
Bibliography: p. 365-408
Includes index
"List of corrections" online (as of Jan. 2014): http://www.stanford.edu/~yyye/book.html
内容説明・目次
内容説明
The first comprehensive review of the theory and practice of one oftoday's most powerful optimization techniques.
The explosive growth of research into and development of interiorpoint algorithms over the past two decades has significantlyimproved the complexity of linear programming and yielded some oftoday's most sophisticated computing techniques. This book offers acomprehensive and thorough treatment of the theory, analysis, andimplementation of this powerful computational tool.
Interior Point Algorithms provides detailed coverage of all basicand advanced aspects of the subject. Beginning with an overview offundamental mathematical procedures, Professor Yinyu Ye movesswiftly on to in-depth explorations of numerous computationalproblems and the algorithms that have been developed to solve them.An indispensable text/reference for students and researchers inapplied mathematics, computer science, operations research,management science, and engineering, Interior Point Algorithms:
* Derives various complexity results for linear and convexprogramming
* Emphasizes interior point geometry and potential theory
* Covers state-of-the-art results for extension, implementation,and other cutting-edge computational techniques
* Explores the hottest new research topics, including nonlinearprogramming and nonconvex optimization.
目次
Geometry of Convex Inequalities.
Computation of Analytic Center.
Linear Programming Algorithms.
Worst-Case Analysis.
Average-Case Analysis.
Asymptotic Analysis.
Convex Optimization.
Nonconvex Optimization.
Implementation Issues.
Bibliography.
Index.
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