- Hezhi Luo
, Xianye Zhang, Huixian Wu, Weiqiang Xu:
Effective algorithms for separable nonconvex quadratic programming with one quadratic and box constraints. Comput. Optim. Appl. 86(1): 199-240 (2023) - Björn Martens
:
Error estimates for Runge-Kutta schemes of optimal control problems with index 1 DAEs. Comput. Optim. Appl. 86(3): 1299-1325 (2023) - Jesús Camacho Moro
, María Josefa Cánovas
, Marco A. López
, Juan Parra
:
Robust and continuous metric subregularity for linear inequality systems. Comput. Optim. Appl. 86(3): 967-988 (2023) - Davide Previtali
, Mirko Mazzoleni
, Antonio Ferramosca
, Fabio Previdi:
GLISp-r: a preference-based optimization algorithm with convergence guarantees. Comput. Optim. Appl. 86(1): 383-420 (2023) - R. Tyrrell Rockafellar
:
Generic linear convergence through metric subregularity in a variable-metric extension of the proximal point algorithm. Comput. Optim. Appl. 86(3): 1327-1346 (2023) - Stefan Schwarze, Oliver Stein
:
A branch-and-prune algorithm for discrete Nash equilibrium problems. Comput. Optim. Appl. 86(2): 491-519 (2023) - Hiroki Tanabe
, Ellen H. Fukuda, Nobuo Yamashita:
An accelerated proximal gradient method for multiobjective optimization. Comput. Optim. Appl. 86(2): 421-455 (2023) - Hoai An Le Thi, Thi-Minh-Tam Nguyen, Tao Pham Dinh:
On solving difference of convex functions programs with linear complementarity constraints. Comput. Optim. Appl. 86(1): 163-197 (2023) - Cheik Traoré
, Saverio Salzo, Silvia Villa
:
Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization. Comput. Optim. Appl. 86(1): 303-344 (2023) - Constantine Alexander Vitt, Darinka Dentcheva
, Andrzej Ruszczynski, Nolan Sandberg:
The deepest event cuts in risk-averse optimization with application to radiation therapy design. Comput. Optim. Appl. 86(3): 1347-1372 (2023) - COAP 2022 Best Paper Prize. Comput. Optim. Appl. 86(3): 1373-1375 (2023)
- Dongdong Zhang, Shaohua Pan, Shujun Bi, Defeng Sun:
Zero-norm regularized problems: equivalent surrogates, proximal MM method and statistical error bound. Comput. Optim. Appl. 86(2): 627-667 (2023)