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Aproximal-Projection Bundle Method for Lagrangian Relaxation, Including Semidefine Programming
Subtitle:Raport Badawczy = Research Report ; RB/60/2006
Creator: Publisher:Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences
Place of publishing: Date issued/created: Description:20 pages ; 21 cm ; Bibliography p. 20
Subject and Keywords:Nondifferentiable optimization ; Optymalizacja niezróżnicowana ; Lagrangian relaxation ; Convex programming ; Programowanie wypukłe ; Proximal bundle methods ; Semidefinite programming ; Relaksacja lagrange'a
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.
Relation:Raport Badawczy = Research Report
Resource type: Detailed Resource Type: Source: Language: Language of abstract: Rights:Creative Commons Attribution BY 4.0 license
Terms of use:Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -
Digitizing institution:Systems Research Institute of the Polish Academy of Sciences
Original in:Library of Systems Research Institute PAS
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