Oqla user's guide

[1]  M. Hestenes Multiplier and gradient methods , 1969 .

[2]  Jack J. Dongarra,et al.  A set of level 3 basic linear algebra subprograms , 1990, TOMS.

[3]  Nicholas J. Higham,et al.  INVERSE PROBLEMS NEWSLETTER , 1991 .

[4]  M. J. D. Powell,et al.  A method for nonlinear constraints in minimization problems , 1969 .

[5]  Jean Charles Gilbert,et al.  Inside Oqla and Qpalm , 2014 .

[6]  A. F. Izmailov,et al.  Newton-Type Methods for Optimization and Variational Problems , 2014 .

[7]  Jack J. Dongarra,et al.  Algorithm 656: an extended set of basic linear algebra subprograms: model implementation and test programs , 1988, TOMS.

[8]  Philip Wolfe,et al.  An algorithm for quadratic programming , 1956 .

[9]  Jack J. Dongarra,et al.  Algorithm 679: A set of level 3 basic linear algebra subprograms: model implementation and test programs , 1990, TOMS.

[10]  R. Rockafellar The multiplier method of Hestenes and Powell applied to convex programming , 1973 .

[11]  Jean Charles Gilbert,et al.  OQLA/QPALM – Convex quadratic optimization solvers using the augmented Lagrangian approach, with an appropriate behavior on infeasible or unbounded problems , 2014 .

[12]  R. Rockafellar Augmented Lagrange Multiplier Functions and Duality in Nonconvex Programming , 1974 .

[13]  Jean Charles Gilbert,et al.  Global linear convergence of an augmented Lagrangian algorithm for solving convex quadratic optimization problems , 2002 .

[14]  Gerardo Toraldo,et al.  On the Solution of Large Quadratic Programming Problems with Bound Constraints , 1991, SIAM J. Optim..

[15]  Floyd J. Gould,et al.  A general saddle point result for constrained optimization , 1973, Math. Program..

[16]  Jean Charles Gilbert,et al.  How the augmented Lagrangian algorithm can deal with an infeasible convex quadratic optimization problem , 2010 .