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Scalable Relaxation Two-Sweep Modulus-Based Matrix Splitting Methods for Vertical LCP.
- Source :
-
Journal of Optimization Theory & Applications . Oct2024, Vol. 203 Issue 1, p714-744. 31p. - Publication Year :
- 2024
-
Abstract
- Based on a new equivalent reformulation, a scalable modulus-based matrix splitting (SMMS) method is proposed to solve the vertical linear complementarity problem (VLCP). By introducing a relaxation parameter and employing the two-sweep technique, we further enhance the scalability of the method, leading to a framework of the scalable relaxation two-sweep modulus-based matrix splitting (SRTMMS) method. To theoretically demonstrate the acceleration of the convergence provided by the SMMS method, we present a comparison theorem for the case of s = 2 . Furthermore, we establish the convergence of the SRTMMS method for arbitrary s. Preliminary numerical results indicate promising performance of the SRTMMS method. [ABSTRACT FROM AUTHOR]
- Subjects :
- *LINEAR complementarity problem
*RELAXATION techniques
*SCALABILITY
Subjects
Details
- Language :
- English
- ISSN :
- 00223239
- Volume :
- 203
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Journal of Optimization Theory & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 180628882
- Full Text :
- https://doi.org/10.1007/s10957-024-02529-9