@misc{Kiwiel_Krzysztof_Aproximal-Projection_2006,
 author={Kiwiel, Krzysztof},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2006},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={The paper presents a proximal bundle method for minimizing a convex function f over a convex set C. It requires evaluating f and its subgradients with a fixed but possibly unknown accuracy ε> 0. Each iteration involves solving an unconstrained proximal subproblem and projecting a certain point onto C. The method asymptotically finds points that are ε-optimal. In Lagrangian relaxation of convex programs, it allows for ε-accurate solutions of Lagrangian subproblems and finds ε-optimal primal solutions. For semidefinite programming problems, it extends the highly successful spectral bundle method to the case of inexact eigenvalue computations.},
 title={Aproximal-Projection Bundle Method for Lagrangian Relaxation, Including Semidefine Programming},
 type={Text},
 URL={http://www.rcin.org.pl/Content/139708/PDF/RB-2006-60.pdf},
 keywords={Nondifferentiable optimization, Optymalizacja niezróżnicowana, Lagrangian relaxation, Convex programming, Programowanie wypukłe, Proximal bundle methods, Semidefinite programming, Relaksacja lagrange'a},
}