A strongly convergent proximal bundle method for convex minimization in Hilbert spaces
From MaRDI portal
Publication:2790873
DOI10.1080/02331934.2015.1004549zbMath1334.49101OpenAlexW2033975747MaRDI QIDQ2790873
Wim van Ackooij, Welington de Oliveira, José Yunier Bello Cruz
Publication date: 8 March 2016
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2015.1004549
Numerical mathematical programming methods (65K05) Convex programming (90C25) Numerical methods based on nonlinear programming (49M37)
Related Items
Two‐agent scheduling with linear resource‐dependent processing times ⋮ Minimizing oracle-structured composite functions ⋮ Target radius methods for nonsmooth convex optimization ⋮ Proximal bundle methods for nonsmooth DC programming ⋮ An Inexact Bundle Algorithm for Nonconvex Nonsmooth Minimization in Hilbert Space ⋮ Nonsmooth optimization by successive abs-linearization in function spaces
Cites Work
- Convex proximal bundle methods in depth: a unified analysis for inexact oracles
- Decomposition approaches for block-structured chance-constrained programs with application to hydro-thermal unit commitment
- Solving the unit commitment problem of hydropower plants via Lagrangian relaxation and sequential quadratic programming
- On approximations with finite precision in bundle methods for nonsmooth optimization
- Divide to conquer: decomposition methods for energy optimization
- Proximity control in bundle methods for convex nondifferentiable minimization
- Convergence of some algorithms for convex minimization
- On the minimum norm solution of linear programs
- A two-stage planning model for power scheduling in a hydro-thermal system under uncertainty
- A descent proximal level bundle method for convex nondifferentiable optimization
- Large-scale unit commitment under uncertainty
- A primal-proximal heuristic applied to the French unit-commitment problem
- Prices stabilization for inexact unit-commitment problems
- A Strongly Convergent Method for Nonsmooth Convex Minimization in Hilbert Spaces
- The Cutting-Plane Method for Solving Convex Programs
- Dual Applications of Proximal Bundle Methods, Including Lagrangian Relaxation of Nonconvex Problems
- Convex analysis and monotone operator theory in Hilbert spaces
