Preconditioned Hybrid Conjugate Gradient Algorithm for P-Laplacian

Abstract

In this paper, a hybrid conjugate gradient algorithm with weighted preconditioner is proposed. The algorithm can efficiently solve the minimizing problem of general function deriving from finite element discretization of the p-Laplacian. The algorithm is efficient, and its convergence rate is mesh-independent. Numerical experiments show that the hybrid conjugate gradient direction of the algorithm is superior to the steepest descent one when $p$ is large.