MASOR

AcronymDefinition
MASORMobility Aid Securement and Occupant Restraint System (motor vechilce device)
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According to the theory of iterative methods, the optimal parameters of the GASOR method and MASOR method are as follows:
To get the optimal values of [alpha], [omega], and [tau] for the GASOR method and [alpha], [beta], and [omega] for the MASOR method, we need to analyze the modulus of eigenvalues of [M.
In this section, numerical examples illustrate the superiority of the GASOR and MASOR methods to the ASOR, SOR-like, GSOR, and MSOR-like methods when they are used for solving the nonsingular saddle point problem (1) and show the advantages of the GASOR and MASOR methods over the GSOR, GSSOR, MSSOR, and GMSSOR methods for solving the singular saddle point problem (1).
All computations for the SOR-like, GSOR, MSOR-like, ASOR, GASOR, and MASOR methods are started from initial vector [x.
In Table 2, for various problem sizes p, we list the theoretical optimal iteration parameters of the SOR-like, GSOR, MSOR-like, ASOR, GASOR, and MASOR methods used in our implementations.
As observed in Table 2, the convergence factors of the GASOR and MASOR methods are smaller than that of the SOR-like method.
From the three figures, we note that the six methods are convergent while the GASOR and MASOR methods converge faster than other methods.
All computations for the GSOR, MSSOR, GSSOR, GMSSOR, GASOR, and MASOR methods are started from initial vector [x.
In Table 4, for various problem sizes p, we list the theoretical optimal iteration parameters of the iteration matrices of the GSOR, MSSOR, GSSOR, GMSSOR, GASOR, and MASOR methods for solving singular saddle point problem.
Comparing the results in Table 4, we observe that the pseudospectral radii of the GASOR and MASOR methods are smaller than those of the MSSOR and GMSSOR methods.
It clearly shows that the six methods are semiconvergent while the GASOR and MASOR methods converge faster.
In this paper, we propose two new methods called GASOR and MASOR methods, respectively, and study the convergence and semiconvergence of these two new methods for solving nonsingular and singular saddle point problems, respectively.