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Lagrangian Relaxation via Ballstep Subgradient Methods
Subtitle:Raport Badawczy = Research Report ; RB/50/2005
Creator:Kiwiel, Krzysztof ; Larsson, Torbjörn ; Lindberg, Per
Publisher:Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences
Place of publishing: Date issued/created: Description:19 pages ; 21 cm ; Bibliography p. 18-19
Subject and Keywords:Optymalizacja ; Nondifferentiable optimization ; Lagrangian relaxation ; Convex programming ; Programowanie wypukłe ; Level projection methods ; Subgradient optimization ; Relaksacja lagrange'a ; Optymalizacja subgradientowa
Abstract:The paper presents useful properties of ballstep subgradient methods for convex optimization that use level controls for estimating the optimal value. Augmented with simple averaging schemes, they asymptotically find objective and constraint subgradients involved in optimality conditions. When applied to Lagrangian relaxation of convex programs, they find both primal and dual solutions, and have practicable stopping criteria. Up till now, similar results have only been known for proximal bundle methods, and for subgradient methods with divergent series stepsizes, whose convergence can be slow. Encouraging numerical results are presented for large-scale nonlinear multicommodity network flow problems.
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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