Andrew R. Conn, Paula K. Coulman, et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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, Paula K. Coulman, et al.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
David Echeverría Ciaurri, Andrew R. Conn, et al.
SPE-IEI 2012
Brage R. Knudsen, Bjarne Foss, et al.
ADCHEM 2012
Caio Merlini Giuliani, Eduardo Camponogara, et al.
Computational and Applied Mathematics