On quadratic convergence of the $$O\left( {\sqrt {nL} } \right)$$ -iteration homogeneous and self‐duallinear programming algorithm

F. Wu, S. Wu and Y. Ye

Annals of Operations Research, 1999, vol. 87, issue 0, 393-406

Abstract: In this paper, we show that Ye‐Todd‐Mizuno's O( $$\sqrt {nL} $$ ) ‐iteration homogeneous andself‐dual linear programming (LP) algorithm possesses quadratic convergence of the duality gap to zero. In the case of infeasibility, this shows that a homogenizing variable quadratically converges to zero (which proves that at least one of the primal and dual LP problems is infeasible) and implies that the iterates of the (original) LP variable quadratically diverge. Thus, we have established a complete asymptotic convergence result for interior‐point algorithms without any assumption on the LP problem. Copyright Kluwer Academic Publishers 1999

Date: 1999
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1018905724427 (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:87:y:1999:i:0:p:393-406:10.1023/a:1018905724427

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

DOI: 10.1023/A:1018905724427

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 ().