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Constraint Aggregation Principle in Convex Optimization


  • Y.M. Ermoliev
  • A.V. Kryazhimskii
  • A. Ruszczynski


A general constraint aggregation technique is proposed for convex optimization problems. At each iteration a set of convex inequalities and linear equations is replaced by a single inequality formed as a linear combination of the original constraints. After solving the simplified subproblem, new aggregation coefficients are calculated and the iteration continues. This general aggregation principle is incorporated into a number of specific algorithms. Convergence of the new methods is proved and speed of convergence analyzed. It is shown that in case of linear programming, the method with aggregation has a polynomial complexity. Finally, application to decomposable problems is discussed.

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  • Y.M. Ermoliev & A.V. Kryazhimskii & A. Ruszczynski, 1995. "Constraint Aggregation Principle in Convex Optimization," Working Papers wp95015, International Institute for Applied Systems Analysis.
  • Handle: RePEc:wop:iasawp:wp95015

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    References listed on IDEAS

    1. A.P. Wierzbicki, 1993. "Augmented Simplex: A Modified and Parallel Version of Simplex Method Based on Multiple Objective and Subdifferential Optimization Approach," Working Papers wp93059, International Institute for Applied Systems Analysis.
    2. Robert E. Bixby, 1992. "Implementing the Simplex Method: The Initial Basis," INFORMS Journal on Computing, INFORMS, vol. 4(3), pages 267-284, August.
    3. A. Ruszczynski, 1993. "Regularized Decomposition of Stochastic Programs: Algorithmic Techniques and Numerical Results," Working Papers wp93021, International Institute for Applied Systems Analysis.
    4. Uwe H. Suhl & Leena M. Suhl, 1990. "Computing Sparse LU Factorizations for Large-Scale Linear Programming Bases," INFORMS Journal on Computing, INFORMS, vol. 2(4), pages 325-335, November.
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    Cited by:

    1. A.V. Kryazhimskii & A. Ruszczynski, 1997. "Constraint Aggregation in Infinite-Dimensional Spaces and Applications," Working Papers ir97051, International Institute for Applied Systems Analysis.
    2. Y.M. Ermoliev & A. Ruszczynski, 1995. "Convex Optimization by Radial Search," Working Papers wp95036, International Institute for Applied Systems Analysis.
    3. R. Rozycki, 1995. "Constraint Aggregation Principle: Application to a Dual Transportation Problem," Working Papers wp95103, International Institute for Applied Systems Analysis.
    4. A.V. Kryazhimskii & V.I. Maksimov & Yu.S. Osipov, 1996. "Reconstruction of Boundary Sources through Sensor Observations," Working Papers wp96097, International Institute for Applied Systems Analysis.
    5. M. Davidson, 1996. "Proximal Point Mappings and Constraint Aggregation Principle," Working Papers wp96102, International Institute for Applied Systems Analysis.
    6. B.V. Digas & Y.M. Ermoliev & A.V. Kryazhimskii, 1998. "Guaranteed Optimization in Insurance of Catastrophic Risks," Working Papers ir98082, International Institute for Applied Systems Analysis.

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