A globally convergent method of moving asymptotes with trust region technique
The method of moving asymptotes is known to work well for certain problems arising in structural optimization. A globally convergent method of moving asymptotes with trust region technique is proposed in this paper. A convex separable subproblem is solved in each iteration. The choice of asymptotes is controlled by the trust region radius such that global convergence of the algorithm is obtained. In addition, preliminary numerical tests are given.
method of moving asymptotes structural optimization trust region method