An Iterative Method for Horizontal Tensor Complementarity Problems

Chen Sun (), Yong Wang () and Zheng-Hai Huang ()
Additional contact information
Chen Sun: Tianjin University
Yong Wang: Tianjin University
Zheng-Hai Huang: Tianjin University

Journal of Optimization Theory and Applications, 2024, vol. 202, issue 2, No 13, 854-877

Abstract: Abstract In this paper, we focus on a class of horizontal tensor complementarity problems (HTCPs). By introducing the block representative tensor, we show that finding a solution of HTCP is equivalent to finding a nonnegative solution of a related tensor equation. We establish the theory of the existence and uniqueness of solution of HTCPs under the proper assumptions. In particular, in the case of the concerned block representative tensor possessing the strong M-property, we propose an algorithm to solve HTCPs by efficiently exploiting the beneficial properties of block representative tensor, and show that the iterative sequence generated by the algorithm is monotone decreasing and converges to a solution of HTCPs. The final numerical experiments verify the correctness of the theory in this paper and show the effectiveness of the proposed algorithm.

Keywords: Horizontal tensor complementarity problem; Tensor equation; Block representative tensor; Monotonically decreasing sequence; Strong M-property; 90C33; 90C30; 65H10 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-024-02450-1 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:202:y:2024:i:2:d:10.1007_s10957-024-02450-1

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

DOI: 10.1007/s10957-024-02450-1

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 ().