Andrew R. Conn, Léa A. Deleris, et al.
Quality and Reliability Engineering International
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.
Andrew R. Conn, Léa A. Deleris, et al.
Quality and Reliability Engineering International
David Echeverría Ciaurri, Andrew R. Conn, et al.
SPE-IEI 2012
Andrew R. Conn, Paula K. Coulman, et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Andreas Wächter, Chandu Visweswariah, et al.
Future Generation Computer Systems