期刊
AIMS MATHEMATICS
卷 7, 期 6, 页码 10994-11014出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2022614
关键词
quasi-complementarity problem; modulus-based iteration method; matrix splitting; convergence
资金
- QingLan Project of Jiangsu Province
- '226' Talent Scientific Research Project of Nantong City
- Science and Technology Project of Nantong City [JC2021198]
This paper investigates an iteration method for large sparse quasi-complementarity problems (QCP) and proposes a general matrix splitting (MMS) iteration method to improve the convergence rate. The convergence analyses are conducted when the system matrix is either an H+-matrix or a positive definite matrix. Numerical experiments show that the proposed method outperforms the MMS iteration method.
For large sparse quasi-complementarity problem (QCP), Wu and Guo [35] recently studied a modulus-based matrix splitting (MMS) iteration method, which belongs to a class of inner-outer iteration methods. In order to improve the convergence rate of the inner iteration so as to get fast convergence rate of the outer iteration, a general MMS (GMMS) iteration method is proposed in this paper. Convergence analyses on the GMMS method are studied in detail when the system matrix is either an H+-matrix or a positive definite matrix. In the case of H+-matrix, weaker convergence condition of the GMMS iteration method is obtained. Finally, two numerical experiments are conducted and the results indicate that the new proposed GMMS method achieves a better performance than the MMS iteration method.
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