logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Realtime Pdeconstrained Optimization Edited By Lorenz T Biegler Omar Ghattas Matthias Heinkenschloss David Keyes And Bart Van Bloemen Waanders

  • SKU: BELL-1374438
Realtime Pdeconstrained Optimization Edited By Lorenz T Biegler Omar Ghattas Matthias Heinkenschloss David Keyes And Bart Van Bloemen Waanders
$ 31.00 $ 45.00 (-31%)

5.0

30 reviews

Realtime Pdeconstrained Optimization Edited By Lorenz T Biegler Omar Ghattas Matthias Heinkenschloss David Keyes And Bart Van Bloemen Waanders instant download after payment.

Publisher: Society for Industrial and Applied Mathematics
File Extension: PDF
File size: 28.67 MB
Pages: 336
Author: Edited by Lorenz T. Biegler; Omar Ghattas; Matthias Heinkenschloss; David Keyes; and Bart van Bloemen Waanders, Lorenz T. Biegler; Omar Ghattas; Matthias Heinkenschloss; David Keyes; and Bart van Bloemen Waanders
ISBN: 9780898716214, 0898716217
Language: English
Year: 2007

Product desciption

Realtime Pdeconstrained Optimization Edited By Lorenz T Biegler Omar Ghattas Matthias Heinkenschloss David Keyes And Bart Van Bloemen Waanders by Edited By Lorenz T. Biegler; Omar Ghattas; Matthias Heinkenschloss; David Keyes; And Bart Van Bloemen Waanders, Lorenz T. Biegler; Omar Ghattas; Matthias Heinkenschloss; David Keyes; And Bart Van Bloemen Waanders 9780898716214, 0898716217 instant download after payment.

...a timely contribution to a field of growing importance. This carefully edited book presents a rich collection of chapters ranging from mathematical methodology to emerging applications. I recommend it to students as a rigorous and comprehensive presentation of simulation-based optimization and to researchers as an overview of recent advances and challenges in the field. Jorge Nocedal, Professor, Northwestern University. Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs and the requirement for rapid solution pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics. Despite difficulties, there is a pressing need to capitalize on continuing advances in computing power to develop optimization methods that will replace simple rule-based decision making with optimized decisions based on complex PDE simulations. Audience The book is aimed at readers who have expertise in simulation and are interested in incorporating optimization into their simulations, who have expertise in numerical optimization and are interested in adapting optimization methods to the class of infinite-dimensional

Related Products