Caio Merlini Giuliani, Eduardo Camponogara, et al.
Computational and Applied Mathematics
A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Numerical results are presented for general quadratic programs.
Caio Merlini Giuliani, Eduardo Camponogara, et al.
Computational and Applied Mathematics
Sonia Cafieri, Andrew R. Conn, et al.
OJMO
Benjamin Reiser, Betty J. Flehinger, et al.
IEEE Transactions on Reliability
Chandu Visweswariah, Ruud A. Haring, et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems