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Perturbation Methods for Saddle Point Computation


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  • M.J. Kallio
  • A. Ruszczynski


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.

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Bibliographic Info

Paper provided by International Institute for Applied Systems Analysis in its series Working Papers with number wp94038.

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Date of creation: May 1994
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Handle: RePEc:wop:iasawp:wp94038

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  1. A. Ruszczynski, 1994. "A Partial Regularization Method for Saddle Point Seeking," Working Papers wp94020, International Institute for Applied Systems Analysis.
  2. M.J. Kallio & A. Ruszczynski, 1994. "Parallel Solution of Linear Programs Via Nash Equilibria," Working Papers wp94015, International Institute for Applied Systems Analysis.
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Cited by:
  1. Flam, Sjur & Ruszczynski, A., 2006. "Computing Normalized Equilibria in Convex-Concave Games," Working Papers 2006:9, Lund University, Department of Economics.
  2. S.D. Flam & A. Ruszczynski, 1994. "Noncooperative Convex Games: Computing Equilibrium By Partial Regularization," Working Papers wp94042, International Institute for Applied Systems Analysis.
  3. M.J. Kallio & C.H. Rosa, 1994. "Large-Scale Convex Optimization via Saddle Point Computation," Working Papers wp94107, International Institute for Applied Systems Analysis.


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