On the Surrogate Gradient Algorithm for Lagrangian Relaxation

@inproceedings{Sun2007OnTS,
  title={On the Surrogate Gradient Algorithm for Lagrangian Relaxation},
  author={Tao Sun and Q. C. Zhao and Peter B. Luh},
  year={2007}
}
When applied to large-scale separable optimization problems, the recently developed surrogate subgradient method for Lagrangian relaxation (Zhao et al.: J. Optim. Theory Appl. 100, 699–712, 1999) does not need to solve optimally all the subproblems to update the multipliers, as the traditional subgradient method requires. Based on it, the penalty surrogate subgradient algorithm was further developed to address the homogenous solution issue (Guan et al.: J. Optim. Theory Appl. 113, 65–82, 2002… CONTINUE READING