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In this paper, we consider the numerical solution of a large complex linear system with a saddle-point form obtained by the discretization of the time-harmonic eddy-current optimal control problem. A new Schur complement is proposed for this algebraic system, extending it to both the block-triangular preconditioner and the structured preconditioner. A theoretical analysis proves that the eigenvalues of block-triangular and structured preconditioned matrices are located in the interval [1/2, 1]. Numerical simulations show that two new preconditioners coupled with a Krylov subspace acceleration have good feasibility and effectiveness and are superior to some existing efficient algorithms. [ABSTRACT FROM AUTHOR]

Abstract For symmetric indefinite linear systems, we introduce a new triangular preconditioner based on symmetric and triangular (ST) decomposition. A new (1, 1) block is obtained by augmented Lagrangian technique. The new ST preconditioner is introduced by the combination of the new (1, 1) block and symmetric and triangular (ST) decomposition. Then a preconditioned system can be obtained by preconditioning technique, which is superior to the original system in terms of condition number. We study the spectral properties of preconditioned system, such as eigenvalues, the estimation of condition number and then give the quasi-optimal parameter. Numerical examples are given to indicate that the new preconditioner has obvious efficiency advantages. Finally, we conclude that the new ST preconditioner is a better option to deal with large and sparse problems. [ABSTRACT FROM AUTHOR]

The successive overrelaxation-like (SOR-like) method with the real parameters ω is considered for solving the augmented system. The new method is called the modified SOR-like (MSOR-like) method. The functional equation between the parameters and the eigenvalues of the iteration matrix of the MSOR-like method is given. Therefore, the necessary and sufficient condition for the convergence of the MSOR-like method is derived. The optimal iteration parameter ω of the MSOR-like method is derived. Finally, the proof of theorem and numerical computation based on a particular linear system are given, which clearly show that the MSOR-like method outperforms the SOR-like (Li, C. J., Li, B. J., and Evans, D. J. Optimum accelerated parameter for the GSOR method. Neural, Parallel & Scientific Computations, 7(4), 453-462 (1999)) and the modified symmetric SOR-like (MSSOR-like) methods (Wu, S. L., Huang, T. Z., and Zhao, X. L. A modified SSOR iterative method for augmented systems. Journal of Computational and Applied Mathematics, 228(4), 424-433 (2009)). [ABSTRACT FROM AUTHOR]