General Form of Nonmonotone Line Search Techniques For Unconstrained Optimization

By using the forcing function, we proposed a general form of nonmonotone line search technique for unconstrained optimization. The technique includes some well known nonmonotone line search as special cases while independence on the nonmonotone parameter. We establish the global convergence of the method under weak conditions and we report the numerical test with a modified BFGS method to show the effectiveness of the proposed method

Global convergence of the nonmonotone MBFGS method for nonconvex unconstrained minimization

AbstractIn this paper, we propose a new nonmonotone Armijo type line search and prove that the MBFGS method proposed by Li and Fukushima with this new line search converges globally for nonconvex minimization. Some numerical experiments show that this nonmonotone MBFGS method is efficient for the given test problems