On the convergence of a predictor-corrector variant algorithm

Rui Jorge Almeida and Arilton Teixeira ()

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2015, vol. 23, issue 2, 418 pages

Abstract: A feasible predictor-corrector Linear Programming variant of Mehrotra’s algorithm, that was shown to have good performance on transportation and assignment problems, was developed by Bastos and Paixão. We prove the theoretical efficiency of this algorithm by showing its polynomial complexity and its superlinear convergence. Copyright Sociedad de Estadística e Investigación Operativa 2015

Keywords: Linear Programming; Predictor-corrector algorithm; Interior-point methods; Mehrotra-type algorithm; Polynomial complexity; Superlinear convergence; MSC 90C51; MSC 90C05 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s11750-014-0346-8 (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:topjnl:v:23:y:2015:i:2:p:401-418

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

DOI: 10.1007/s11750-014-0346-8

Access Statistics for this article

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Juan José Salazar González and Gustavo Bergantiños

More articles in TOP: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().