Subspace SSOR methods for a class of generalized linear complementarity problem

Ge Li; Jicheng Li

doi:10.1007/s12597-026-01191-1

Subspace SSOR methods for a class of generalized linear complementarity problem

Ge Li
, Jicheng Li

Xi'an Technological University
School of Mathematics and Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we introduce a class of generalized linear complementarity problem(G-LCP), which only needs to satisfy the complementarity condition in a nonempty index set. Then, we propose subspace SSOR methods to solve G-LCP and prove that the iterations are contractions. It is pointed out that G-LCP can be applied to some convex quadratic programming problems. Numerical examples are tested to illustrate the efficiency of our proposed methods.

Original language	English
Journal	OPSEARCH
DOIs	https://doi.org/10.1007/s12597-026-01191-1
State	Accepted/In press - 2026
Externally published	Yes

Keywords

Convergence analysis
Convex quadratic programming
Generalized linear complementarity problem
Subspace SSOR methods

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10.1007/s12597-026-01191-1

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title = "Subspace SSOR methods for a class of generalized linear complementarity problem",

abstract = "In this paper, we introduce a class of generalized linear complementarity problem(G-LCP), which only needs to satisfy the complementarity condition in a nonempty index set. Then, we propose subspace SSOR methods to solve G-LCP and prove that the iterations are contractions. It is pointed out that G-LCP can be applied to some convex quadratic programming problems. Numerical examples are tested to illustrate the efficiency of our proposed methods.",

keywords = "Convergence analysis, Convex quadratic programming, Generalized linear complementarity problem, Subspace SSOR methods",

author = "Ge Li and Jicheng Li",

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PY - 2026

Y1 - 2026

N2 - In this paper, we introduce a class of generalized linear complementarity problem(G-LCP), which only needs to satisfy the complementarity condition in a nonempty index set. Then, we propose subspace SSOR methods to solve G-LCP and prove that the iterations are contractions. It is pointed out that G-LCP can be applied to some convex quadratic programming problems. Numerical examples are tested to illustrate the efficiency of our proposed methods.

AB - In this paper, we introduce a class of generalized linear complementarity problem(G-LCP), which only needs to satisfy the complementarity condition in a nonempty index set. Then, we propose subspace SSOR methods to solve G-LCP and prove that the iterations are contractions. It is pointed out that G-LCP can be applied to some convex quadratic programming problems. Numerical examples are tested to illustrate the efficiency of our proposed methods.

KW - Convergence analysis

KW - Convex quadratic programming

KW - Generalized linear complementarity problem

KW - Subspace SSOR methods

UR - https://www.scopus.com/pages/publications/105040701037

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JO - OPSEARCH

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Subspace SSOR methods for a class of generalized linear complementarity problem

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Keywords

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