Tittle: Anderson acceleration of the modulus-based matrix splitting algorithms for horizontal nonlinear complementarity systems
Abstract: In this paper, enlightened by the effectiveness of Anderson acceleration (AA), a well-established technique for accelerating fixed-point solvers, we first present the Anderson accelerating modulus-based matrix splitting (AAMS) algorithms for a class of horizontal nonlinear complementarity problems. Then, by introducing the strong semi-smoothness of the absolute value function, we establish the local convergence theory of the AAMS algorithms. More importantly, we provide the optimal parameter for the AAMS algorithms, which is independent of iteration and applicable to other reduced MS algorithms. Finally, the numerical experiments are conducted to clarify the efficiency and practicability of the AAMS algorithms and its optimal parameter, and the effects of two parameters (both derived from AA) of the AAMS algorithms are analyzed.
Citation: Li, Z, Zhang, H. Anderson acceleration of the modulus-based matrix splitting algorithms for horizontal nonlinear complementarity systems. Numer Linear Algebra Appl. 2022; 29( 5):e2438.
