A subspace derivative-free projection method for convex constrained nonlinear equations
摘要
In recent years, there have been many studies on the subspace conjugate gradient methods for solving unconstrained optimization problems. Based on these methods and the projection technique, in this paper a subspace derivative-free projection method is proposed to solve large-scale nonlinear equations with convex constraints. The search direction is computed by minimizing a quadratic approximation model of the objective function in a three-dimensional subspace. Under the monotonicity and Lipschitz continuity, the global convergence of the proposed method is proved. Numerical results show that the proposed method is very effective.