Modulus-based matrix splitting algorithms for generalized complex-valued horizontal linear complementarity problems

In this paper, we introduce the complex-valued horizontal linear complementarity problem (CHLCP), we provide two equivalent real-valued reformulations, and study modulus-based matrix splitting algorithms for solving the CHLCP. This latter point is motivated by the recent introduction of modulus-based matrix splitting methods for (non-horizontal) complex linear complementarity problems (CLCPs), which we generalize. We study the convergence of the proposed algorithms. Whenever possible, we seek convergence conditions that are directly based on the form of the real and imaginary parts of the matrices of the CHLCP in its complex form. This makes the convergence easier to evaluate than in existing convergence analyses. Finally, we study the numerical properties of the proposed algorithms by solving several CHLCPs. In this context, we also revisit results on the CLCP under the larger CHLCP framework, providing new numerical insights on the efficiency of existing algorithms for the CLCP.

Authors

Institutions

Publication Details

Journal
Journal of Computational and Applied Mathematics
Published
2024-12-12
DOI
https://doi.org/10.1016/j.cam.2024.116440
Citations
3
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
1.08

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modulus-based matrix splitting algorithms for generalized complex-valued horizontal linear complementarity problems

Emanuele Galligani, Francesco Mezzadri
3 citations
Journal of Computational and Applied Mathematics
Matrix Theory and Algorithms
1.08
article

Modulus-based matrix splitting algorithms for generalized complex-valued horizontal linear complementarity problems

Emanuele Galligani, Francesco Mezzadri
article en
3 citations

Abstract

In this paper, we introduce the complex-valued horizontal linear complementarity problem (CHLCP), we provide two equivalent real-valued reformulations, and study modulus-based matrix splitting algorithms for solving the CHLCP. This latter point is motivated by the recent introduction of modulus-based matrix splitting methods for (non-horizontal) complex linear complementarity problems (CLCPs), which we generalize. We study the convergence of the proposed algorithms. Whenever possible, we seek convergence conditions that are directly based on the form of the real and imaginary parts of the matrices of the CHLCP in its complex form. This makes the convergence easier to evaluate than in existing convergence analyses. Finally, we study the numerical properties of the proposed algorithms by solving several CHLCPs. In this context, we also revisit results on the CLCP under the larger CHLCP framework, providing new numerical insights on the efficiency of existing algorithms for the CLCP.

Journal of Computational and Applied MathematicsVol. 460
University of Modena and Reggio Emilia (IT)
Università Degli Studi di Modena e Reggio Emila, Istituto Nazionale di Alta Matematica "Francesco Severi", Gruppo Nazionale per il Calcolo Scientifico
Openalex Percentile: Top 19%
Matrix Theory and Algorithms
1.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Modulus-based matrix splitting algorithms for generalized complex-valued horizontal linear complementarity problems — Emanuele Galligani, Francesco Mezzadri · Journal of Computational and Applied Mathematics (2024) | TGRS Research Map | TGRS