Skip to main content

Advertisement

Log in

Parallel splitting augmented Lagrangian methods for monotone structured variational inequalities

  • Published:
Computational Optimization and Applications Aims and scope Submit manuscript

Abstract

The typical structured variational inequalities can be interpreted as a system of equilibrium problems with a leader and two cooperative followers. Assume that, based on the instruction given by the leader, each follower can solve the individual equilibrium sub-problems in his own way. The responsibility of the leader is to give a more reasonable instruction for the next iteration loop based on the feedback information from the followers. This consideration leads us to present a parallel splitting augmented Lagrangian method (abbreviated to PSALM). The proposed method can be extended to solve the system of equilibrium problems with three separable operators. Finally, it is explained why we cannot use the same technique to develop similar methods for problems with more than three separable operators.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Auslender, A., Teboulle, M., Ben-Tiba, S.: A logarithmic-quadratic proximal method for variational inequalities. Comput. Optim. Appl. 12, 31–40 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  2. Chen, G., Teboulle, M.: A proximal-based decomposition method for convex minimization problems. Math. Programm. 64, 81–101 (1994)

    Article  MathSciNet  Google Scholar 

  3. Facchinei, F., Pang, J.-S.: Finite-Dimensional Variational Inequalities and Complementarity Problems, vol. I, Springer Series in Operations Research. Springer, New York (2003)

    Google Scholar 

  4. Fukushima, M.: Application of the alternating direction method of multipliers to separable convex programming problems. Comput. Optim. Appl. 1, 93–111 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  5. Gabay, D.: Applications of the method of multipliers to variational inequalities. In: Fortin, M., Glowinski, R. (eds.) Augmented Lagrange Methods: Applications to the Solution of Boundary-Valued Problems, pp. 299–331. North-Holland, Amsterdam (1983)

    Chapter  Google Scholar 

  6. Gabay, D., Mercier, B.: A dual algorithm for the solution of nonlinear variational problems via finite-element approximations. Comput. Math. Appl. 2, 17–40 (1976)

    Article  MATH  Google Scholar 

  7. Glowinski, R.: Numerical Methods for Nonlinear Variational Problems. Springer, New York (1984)

    MATH  Google Scholar 

  8. Glowinski, R., Le Tallec, P.: Augmented Lagrangian and Operator-Splitting Methods in Nonlinear Mechanics. SIAM Studies in Applied Mathematics. SIAM, Philadelphia (1989)

    MATH  Google Scholar 

  9. Martinet, B.: Regularization d’inéquations variationelles par approximations successives. Rev. Francaise Inform. Rech. Opér. 4, 154–159 (1970)

    MathSciNet  Google Scholar 

  10. Nocedal, J., Wright, S.J.: Numerical Optimization, 2nd edn. Springer, Berlin (2006)

    MATH  Google Scholar 

  11. Rockafellar, R.T.: Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14, 877–898 (1976)

    Article  MATH  MathSciNet  Google Scholar 

  12. Teboulle, M.: Convergence of proximal-like algorithms. SIAM J. Optim. 7, 1069–1083 (1997)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bing-Sheng He.

Rights and permissions

Reprints and permissions

About this article

Cite this article

He, BS. Parallel splitting augmented Lagrangian methods for monotone structured variational inequalities. Comput Optim Appl 42, 195–212 (2009). https://doi.org/10.1007/s10589-007-9109-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10589-007-9109-x

Keywords

Navigation