Numerical optimization: theoretical and practical aspects JF Bonnans, JC Gilbert, C Lemaréchal, CA Sagastizábal Springer Science & Business Media, 2006 | 2220 | 2006 |
Practical aspects of the Moreau--Yosida regularization: Theoretical preliminaries C Lemaréchal, C Sagastizábal SIAM journal on optimization 7 (2), 367-385, 1997 | 316 | 1997 |
Optimisation Numérique-Aspects théoriques et pratiques JF Bonnans, JC Gilbert, C Lemaréchal, C Sagastizábal Springer Verlag, Berlin, 1997 | 237 | 1997 |
Variable metric bundle methods: from conceptual to implementable forms C Lemaréchal, C Sagastizábal Mathematical Programming 76, 393-410, 1997 | 233 | 1997 |
A family of variable metric proximal methods JF Bonnans, JC Gilbert, C Lemaréchal, CA Sagastizábal Mathematical Programming 68, 15-47, 1995 | 180 | 1995 |
The 𝒰-Lagrangian of a convex function C Lemaréchal, F Oustry, C Sagastizábal Transactions of the American mathematical Society 352 (2), 711-729, 2000 | 167 | 2000 |
A redistributed proximal bundle method for nonconvex optimization W Hare, C Sagastizábal SIAM Journal on Optimization 20 (5), 2442-2473, 2010 | 144 | 2010 |
Solving the unit commitment problem of hydropower plants via Lagrangian relaxation and sequential quadratic programming EC Finardi, EL Silva, C Sagastizŕbal Computational & applied mathematics 24, 317-342, 2005 | 143 | 2005 |
Computing proximal points of nonconvex functions W Hare, C Sagastizábal Mathematical Programming 116 (1), 221-258, 2009 | 142 | 2009 |
Bundle methods in stochastic optimal power management: A disaggregated approach using preconditioners L Bacaud, C Lemaréchal, A Renaud, C Sagastizábal Computational Optimization and Applications 20, 227-244, 2001 | 138 | 2001 |
Divide to conquer: decomposition methods for energy optimization C Sagastizábal Mathematical programming 134 (1), 187-222, 2012 | 134 | 2012 |
Inexact bundle methods for two-stage stochastic programming W Oliveira, C Sagastizábal, S Scheimberg SIAM Journal on Optimization 21 (2), 517-544, 2011 | 127 | 2011 |
Convex proximal bundle methods in depth: a unified analysis for inexact oracles W de Oliveira, C Sagastizábal, C Lemaréchal Mathematical Programming 148, 241-277, 2014 | 122 | 2014 |
An infeasible bundle method for nonsmooth convex constrained optimization without a penalty function or a filter C Sagastizábal, M Solodov SIAM Journal on Optimization 16 (1), 146-169, 2005 | 117 | 2005 |
Level bundle methods for oracles with on-demand accuracy W de Oliveira, C Sagastizábal Optimization Methods and Software 29 (6), 1180-1209, 2014 | 113 | 2014 |
A VU-algorithm for convex minimization R Mifflin, C Sagastizabal Mathematical Programming 104 (2), 583-608, 2005 | 113 | 2005 |
A bundle-filter method for nonsmooth convex constrained optimization E Karas, A Ribeiro, C Sagastizábal, M Solodov Mathematical Programming 116 (1), 297-320, 2009 | 111 | 2009 |
A proximal bundle method for nonsmooth nonconvex functions with inexact information W Hare, C Sagastizábal, M Solodov Computational Optimization and Applications 63, 1-28, 2016 | 104 | 2016 |
The volume algorithm revisited: relation with bundle methods L Bahiense, N Maculan, C Sagastizábal Mathematical Programming 94, 41-69, 2002 | 103 | 2002 |
ε-Enlargements of Maximal Monotone Operators: Theory and Applications RS Burachik, CA Sagastizábal, BF Svaiter Reformulation: nonsmooth, piecewise smooth, semismooth and smoothing methods …, 1999 | 98 | 1999 |