A self-adaptive projection method for nonlinear monotone equations with convex constraints

In this paper, we propose a self-adaptive derivative-free projection method for solving large-scale nonlinear monotone equations with convex constraints. The search direction satisfies the sufficient descent property, which is independent of any line search. Based on Lipschitz continuity and monotonicity proposed shown to be globally convergent. Moreover, numerical results are reported show effectiveness by comparing existing current methods.