A penalty-free-type nonmonotone trust-region method for nonlinear constrained optimization

摘要

In this paper, we propose a penalty-free-type nonmonotone trust region method for solving general nonlinear programming problem. The algorithmic framework yields global convergence without using any penalty function. We analyze the global convergence of the main algorithm for the degenerate problems and also give the globally convergent results under the linear independence constraint qualification. The preliminary numerical tests are reported.