A Full-Newton Step Infeasible Interior-Point Method for the Special Weighted Linear Complementarity Problem

Xiaoni Chi () and Guoqiang Wang ()
Additional contact information
Xiaoni Chi: Guilin University of Electronic Technology
Guoqiang Wang: Shanghai University of Engineering Science

Journal of Optimization Theory and Applications, 2021, vol. 190, issue 1, No 5, 108-129

Abstract: Abstract As an extension of the complementarity problem (CP), the weighted complementarity problem (wCP) is a large class of equilibrium problems with wide applications in science, economics, and engineering. If the weight vector is zero, the wCP reduces to a CP. In this paper, we present a full-Newton step infeasible interior-point method (IIPM) for the special weighted linear complementarity problem over the nonnegative orthant. One iteration of the algorithm consists of one feasibility step followed by a few centering steps. All of them are full-Newton steps, and hence, no calculation of the step size is necessary. The iteration bound of the algorithm is as good as the best-known polynomial complexity of IIPMs for linear optimization.

Keywords: Weighted linear complementarity problem; Infeasible interior-point method; Full-Newton step; Polynomial complexity; 90C51; 90C33 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01873-4 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:190:y:2021:i:1:d:10.1007_s10957-021-01873-4

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

DOI: 10.1007/s10957-021-01873-4

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 ().