AN AFFINE SCALING DERIVATIVE-FREE TRUST REGION METHOD WITH INTERIOR BACKTRACKING TECHNIQUE FOR BOUNDED-CONSTRAINED NONLINEAR PROGRAMMING

This paper proposes an affine scaling derivative-free trust region method with interior backtracking technique for bounded-constrained nonlinear programming.This method is designed to get a stationary point for such a problem with polynomial interpolation models instead of the objective function in trust region subproblem.Combined with both trust region strategy and line search technique,at each iteration,the affine scaling derivative-free trust region subproblem generates a backtracking direction in order to obtain a new accepted interior feasible step.Global convergence and fast local convergence properties are established under some reasonable conditions.Some numerical results are also given to show the effectiveness of the proposed algorithm.