A nonmonotone strategy for solving nonlinear systems of equations is introduced. The idea consists of combining eecient local methods with an algorithm that reduces monotonically the squared norm of the system in a proper way. The local methods used are Newton's method and two quasi-Newton algorithms. Global iterations are based on recently introduced box-constrained minimization algorithms. We...

We address the solution of convex constrained nonlinear systems by new linesearch Quasi-Newton methods. These methods are based on a proper use of the projection map onto the constraint set and on a derivativefree and nonmonotone linesearch strategy. The convergence properties of the proposed methods are presented along with a worst-case iteration complexity bound. Several implementations of th...

Quasi-Newton methods based on least change secant updating formulas that solve linear equations Ax = b in n = dim(x) = dim(b) steps can be expected to solve corresponding smooth nonlinear systems n-step quadratically, i.e. with an r-order of ρ = 2 = 1 + 1/n+O(1/n). The best rate one can possibly expect on general problems is given by the positive root ρn of ρ (ρ− 1) = 1, for which ρn − 1 = ln(n...