EconPapers    
Economics at your fingertips  
 

New Complexity Analysis of the Primal—Dual Newton Method for Linear Optimization

J. Peng (), C. Roos () and T. Terlaky ()

Annals of Operations Research, 2000, vol. 99, issue 1, 23-39

Abstract: We deal with the primal–dual Newton method for linear optimization (LO). Nowadays, this method is the working horse in all efficient interior point algorithms for LO, and its analysis is the basic element in all polynomiality proofs of such algorithms. At present there is still a gap between the practical behavior of the algorithms and the theoretical performance results, in favor of the practical behavior. This is especially true for so-called large-update methods. We present some new analysis tools, based on a proximity measure introduced by Jansen et al., in 1994, that may help to close this gap. This proximity measure has not been used in the analysis of large-update methods before. The new analysis does not improve the known complexity results but provides a unified way for the analysis of both large-update and small-update methods. Copyright Kluwer Academic Publishers 2000

Keywords: linear optimization; interior-point method; primal–dual method; proximity measure; polynomial complexity (search for similar items in EconPapers)
Date: 2000
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1019280614748 (text/html)
Access to full text is restricted to subscribers.

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:annopr:v:99:y:2000:i:1:p:23-39:10.1023/a:1019280614748

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/A:1019280614748

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:annopr:v:99:y:2000:i:1:p:23-39:10.1023/a:1019280614748