Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Robust Optimization (Princeton Series in Applied Mathematics)

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Aharon Ben-Tal 作者
Princeton University Press
譯者
2009-08-10 出版日期
564 頁數
USD 65.00 價格
Hardcover
叢書系列
9780691143682 圖書編碼

Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 圖書標籤: Optimization  數學  優化  機器學習  應用數學   


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Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 著者簡介


Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 著者簡介


Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Robust Optimization (Princeton Series in Applied Mathematics) 在線電子書 圖書描述

Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. "Robust Optimization" is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and, to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, "Robust Optimization" also makes an ideal graduate textbook on the subject.

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