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Comments on “Surrogate Gradient Algorithm for Lagrangian Relaxation”

  • T. S. Chang
Technical Note

Abstract

This note presents not only a surrogate subgradient method, but also a framework of surrogate subgradient methods. Furthermore, the framework can be used not only for separable problems, but also for coupled subproblems. The note delineates such a framework and shows that the algorithm can converges for a larger stepsize.

Keywords

Nondifferentiable optimization Lagrangian relaxation Surrogate subgradient method Subgradient method 

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References

  1. 1.
    Zhao, X., Luh, P.B., Wang, J.: Surrogate gradient algorithm for Lagrangian relaxation. J. Optim. Theory Appl. 100(3), 699–712 (1999) MATHCrossRefMathSciNetGoogle Scholar
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    Guan, X.H., Zhai, Q.Z., Lai, F.: New Lagrangian relaxation based algorithm for resource scheduling with homogeneous subproblems. J. Optim. Theory Appl. 113(1), 65–82 (2002) MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Goffin, J., Kiwiel, K.C.: Convergence of a simple subgradient level method. Math. Program. 85, 207–211 (1999) MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of CaliforniaDavisUSA

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