A relaxed block-triangular splitting preconditioner for generalized saddle-point problems

For the generalized saddle-point problems, based on a new block-triangular splitting of the saddle-point matrix, we introduce a relaxed block-triangular splitting preconditioner to accelerate the convergence rate of the Krylov subspace methods. This new preconditioner is easily implemented since it has simple block structure. The spectral property of the preconditioned matrix is analysed. Moreover, the degree of the minimal polynomial of the preconditioned matrix is also discussed. Numerical experiments are reported to show the preconditioning effect of the new preconditioner.