Introduction

Alexander J. Zaslavski
Additional contact information
Alexander J. Zaslavski: The Technion – Israel Institute of Technology

Chapter Chapter 1 in Numerical Optimization with Computational Errors, 2016, pp 1-9 from Springer

Abstract: Abstract In this book we study behavior of algorithms for constrained convex minimization problems in a Hilbert space. Our goal is to obtain a good approximate solution of the problem in the presence of computational errors. We show that the algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant. In this section we discuss several algorithms which are studied in the book.

Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-30921-7_1

Ordering information: This item can be ordered from
http://www.springer.com/9783319309217

DOI: 10.1007/978-3-319-30921-7_1

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().