A conic trust-region method for optimization with nonlinear equality and inequality constrains via active-set strategy

摘要

In this paper, by means of an active-set strategy, we present a new trust-region method based on conic model for mixed constrained nonlinear programming. The global convergence of the trust-region method is proved under standard conditions. In this paper, one approximate method is also considered to solve the trust region subproblem. As we can see, sufficient decrease of the predicted reduction can be guaranteed by the approximate method. The numerical tests show the effectiveness of the algorithm.