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

Convex And Stochastic Optimization Jf Bonnans

Name: Convex And Stochastic Optimization Jf Bonnans
SKU: BELL-9969976
Price: 31.00 USD
Availability: InStock
Rating: 5 (98 reviews)

SKU: BELL-9969976

$ 31.00 ~~$ 45.00~~ (-31%)

5.0

98 reviews

Convex And Stochastic Optimization Jf Bonnans instant download after payment.

Publisher: Springer

File Extension: PDF

File size: 3.81 MB

Pages: 320

Author: J.F. Bonnans

ISBN: 9783030149772, 3030149773

Language: English

Year: 2019

Product desciption

Convex And Stochastic Optimization Jf Bonnans by J.f. Bonnans 9783030149772, 3030149773 instant download after payment.

This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting. It introduces and analyses the main algorithms for stochastic programs, while the theoretical aspects are carefully dealt with.
The reader is shown how these tools can be applied to various fields, including approximation theory, semidefinite and second-order cone programming and linear decision rules.
This textbook is recommended for students, engineers and researchers who are willing to take a rigorous approach to the mathematics involved in the application of duality theory to optimization with uncertainty.