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2015-07-22
This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way.

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Editorial ReviewsBook Descriptiona carefully selected group of methods for unconstrained and bound constrained optimization problems is analyzed in depth both theoretically and algorithmically. The book focuses on clarity in algorithmic description and analysis rather than generality, and also provides pointers to the literature for the most general theoretical results and robust software,

About the AuthorC.T. Kelley is a Professor in the Department of Mathematics and Center for Research in Scientific Computation at North Carolina State University. He is a member of the editorial board of the SIAM Journal on Optimization, and the SIAM Journal on Numerical Analysis and is the author of over 100 papers and proceedings articles on numerical and computational mathematics.

Product Details
  • Series: Frontiers in Applied Mathematics (Book 18)
  • Paperback: 196 pages
  • Publisher: Society for Industrial and Applied Mathematics; 1 edition (January 1, 1987)
  • Language: English
  • ISBN-10: 0898714338
  • ISBN-13: 978-0898714333







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2015-7-23 17:08:43
die得待遇优化
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2015-7-24 05:04:11
学习学习。
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2015-8-13 20:59:56
see...............
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2018-12-16 18:04:50
感谢分享,迭代法是我工作中用到的理论中最频繁的
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2020-2-11 17:04:46
Thanks for sharing
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