Perturbation Methods for Saddle Point Computation

Kallio, M.J. & Ruszczynski, A. (1994). Perturbation Methods for Saddle Point Computation. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-94-038

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A general class of iterative methods for saddle point seeking is developed. The directions used are subgradients evaluated at perturbed points. Convergence of the methods is proved and alternative strategies for implementation are discussed. The procedure suggests scalable algorithms for solving large-scale linear programs via saddle points. For illustration, some encouraging tests with the standard Lagrangian of linear programs from the Netlib library are reported.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Optimization under Uncertainty (OPT)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:04
Last Modified: 27 Aug 2021 17:14

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