• Yun, Jae Heon (Department of Mathematics, College of Natural Sciences Chungbuk National University)
  • Received : 2015.04.10
  • Published : 2016.05.01


In this paper, we first introduce two one-parameter relaxation (OPR) iterative methods for solving singular saddle point problems whose semi-convergence rate can be accelerated by using scaled preconditioners. Next we present formulas for finding their optimal parameters which yield the best semi-convergence rate. Lastly, numerical experiments are provided to examine the efficiency of the OPR methods with scaled preconditioners by comparing their performance with the parameterized Uzawa method with optimal parameters.


Supported by : National Research Foundation of Korea (NRF)


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