Large-Neighborhood Infeasible Predictor–Corrector Algorithm for Horizontal Linear Complementarity Problems over Cartesian Product of Symmetric Cones

Soodabeh Asadi (), Hossein Mansouri (), Zsolt Darvay (), Maryam Zangiabadi () and Nezam Mahdavi-Amiri ()
Additional contact information
Soodabeh Asadi: Shahrekord University
Hossein Mansouri: Shahrekord University
Zsolt Darvay: Babes-Bolyai University
Maryam Zangiabadi: Shahrekord University
Nezam Mahdavi-Amiri: Sharif University of Technology

Journal of Optimization Theory and Applications, 2019, vol. 180, issue 3, No 8, 829 pages

Abstract: Abstract We present an infeasible interior-point predictor–corrector algorithm, based on a large neighborhood of the central path, for horizontal linear complementarity problem over the Cartesian product of symmetric cones. Throughout the paper, we assume that a certain property holds for the above-mentioned problem. This condition is equivalent to the property of sufficiency for the particular case of horizontal linear complementarity problem. The polynomial convergence is shown for the commutative class of search directions. We specialize our algorithm further by prescribing some scaling elements and also consider the case of feasible starting points. We believe this to be the first interior-point method based on large neighborhoods for the problem in consideration.

Keywords: Horizontal linear complementarity problem; Infeasible interior-point method; Large neighborhood; Euclidean Jordan algebra (EJA); Cartesian product of symmetric cones; 90C33; 90C51 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10957-018-1402-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:joptap:v:180:y:2019:i:3:d:10.1007_s10957-018-1402-6

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-018-1402-6

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().