The convergence of parallel iteration algorithms for linear complementarity problems

For the linear complementarity problem, we set up a class of parallel matrix multisplitting accelerated overrelaxation (AOR) algorithm suitable to multiprocessor systems (SIMD-systems). This new algorithm, when its relaxation parameters are suitably chosen, can not only afford extensive choices for parallely serving the linear complementarity problems, but also can greatly improve the convergence property of itself. When the system matrices of the problems are either H-matrices with positive diagonal elements or symmetric positive definite matrices, we establish convergence theories of the new algorithm in a detailed manner.