On the two-stage multisplitting iteration methods for linear complementarity problems
In this work, the two-stage multisplitting iteration methods based on the equivalent modulus equations are analyzed for solving linear complementarity problems. New convergence results are presented where the convergence domains of the parameter matrices are enlarged compared the existing literature...
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| Vydané v: | Applied mathematics and computation Ročník 475; s. 128741 |
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15.08.2024
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| Abstract | In this work, the two-stage multisplitting iteration methods based on the equivalent modulus equations are analyzed for solving linear complementarity problems. New convergence results are presented where the convergence domains of the parameter matrices are enlarged compared the existing literatures. Furthermore, the improved domains are validated by numerical examples with parallel computations using OpenACC.
•Propose two convergence theorems of the two-stage multisplitting iteration methods for LCPs with new proof techniques.•The given results can improve the domain of the parameter matrices in the existing literatures.•Design an OpenACC framework where the efficiency of the proposed methods is shown to be improved with good speedups. |
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| AbstractList | In this work, the two-stage multisplitting iteration methods based on the equivalent modulus equations are analyzed for solving linear complementarity problems. New convergence results are presented where the convergence domains of the parameter matrices are enlarged compared the existing literatures. Furthermore, the improved domains are validated by numerical examples with parallel computations using OpenACC.
•Propose two convergence theorems of the two-stage multisplitting iteration methods for LCPs with new proof techniques.•The given results can improve the domain of the parameter matrices in the existing literatures.•Design an OpenACC framework where the efficiency of the proposed methods is shown to be improved with good speedups. |
| ArticleNumber | 128741 |
| Author | Zheng, Hua Zhang, Yongxiong Lu, Xiaoping Guo, Wenxiu |
| Author_xml | – sequence: 1 givenname: Wenxiu surname: Guo fullname: Guo, Wenxiu organization: School of Computer Science and Engineering, Macau University of Science and Technology, Macau, PR China – sequence: 2 givenname: Hua orcidid: 0000-0002-2822-0078 surname: Zheng fullname: Zheng, Hua organization: School of Mathematics and Statistics, Shaoguan University, Shaoguan, PR China – sequence: 3 givenname: Xiaoping surname: Lu fullname: Lu, Xiaoping email: xplu@must.edu.mo organization: School of Computer Science and Engineering, Macau University of Science and Technology, Macau, PR China – sequence: 4 givenname: Yongxiong surname: Zhang fullname: Zhang, Yongxiong organization: School of Engineering, Guangzhou College of Technology and Business, Guangzhou, PR China |
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| Cites_doi | 10.1137/S0895479897324032 10.1080/03081087.2018.1470602 10.1016/j.camwa.2018.10.040 10.4208/jcm.1403-m4195 10.1002/nla.1835 10.1016/j.camwa.2019.06.012 10.1002/nla.2319 10.1007/s10092-019-0307-6 10.1007/s10957-016-0944-8 10.1002/nla.680 10.1016/0024-3795(89)90074-8 10.1007/s11075-012-9566-x 10.1137/S0036144595285963 10.1016/j.aml.2013.06.015 10.4208/eajam.261215.220217a 10.1007/s11590-021-01781-6 10.1007/s10957-013-0362-0 10.1007/s11075-022-01436-2 10.1007/BF01385865 10.1007/s11075-019-00799-3 |
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