Skip to main content
Log in

Parallel Interior Point Schemes for Solving Multistage Convex Programming

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The predictor–corrector interior-point path-following algorithm is promising in solving multistage convex programming problems. Among many other general good features of this algorithm, especially attractive is that the algorithm allows possibility to parallelise the major computations. The dynamic structure of the multistage problems specifies a block-tridiagonal system at each Newton step of the algorithm. A wrap-around permutation is then used to implement the parallel computation for this step.

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. P. Arbenz, A. Cleary, J. Dongarra and M. Hegland, LAPACK Working Note No. 142: A comparison of parallel solvers for diagonally dominant and general narrow-banded linear systems, Technical Report CS-99-414, Computer Science Department, University of Tennessee at Knoxville (February 1999).

    Google Scholar 

  2. P. Arbenz and M. Hegland, The stable parallel solution of general narrow banded linear systems, in: High Performance Algorithms for Structured Matrix Problems, eds. P. Arbenz, M. Paprzycki, A. Sameh and V. Sarin (Nova Science, Commack, NY, 1998) pp. 47–73

    Google Scholar 

  3. C.R. Dun, M. Hegland and M.R. Osborne, Parallel stable solution methods for tridiagonal linear systems of equations, in: Computational Techniques and Applications: CTAC '95, eds.A. Easton and R. May (World Scientific, Singapore, 1995).

    Google Scholar 

  4. L.J. Lustig, R.E. Marsten and D.F. Shanno, On implementing Mehrotra's predictor-corrector interior point method for linear programming, SIAM Journal on Optimization 2 (1992) 435–449.

    Google Scholar 

  5. K. Mathur and D. Solow, Management Science (Prentice-Hall, Englewood Cliffs, NJ, 1994).

    Google Scholar 

  6. K. McShane, C. Monma and D.F. Shanno, An implementation of a primal-dual interior point method for linear programming, ORSA Journal on Computing 1 (1989) 70–83.

    Google Scholar 

  7. S. Mehrotra, On the implementation of a primal-dual interior point method, SIAM Journal on Optimization 2 (1992) 575–601.

    Google Scholar 

  8. S. Mizuno, M. Todd and Y. Ye, On adaptive step primal-dual interior-point algorithm for linear programming, Mathematics of Operations Research 18 (1993) 964–981.

    Google Scholar 

  9. J.M. Ortega, Introduction to Parallel and Vector Solution of Linear Systems (Plenum Press, New York, 1988).

    Google Scholar 

  10. M.R. Osborne, Wrap-around partitioning for bi-diagonal systems, Technical Report, Australian National University, Dept. of Mathematics, Australia (1995).

    Google Scholar 

  11. R.T. Rockafellar, Multistage convex programming and discrete-time optimal control, Control and Cybernetics 17 (1988) 225–245.

    Google Scholar 

  12. R.T. Rockafellar and R.-J. B. Wets, Generalized linear quadratic problems of deterministic and stochastic optimal control in discrete time, SIAM J. Control and Optimization 28 (1990) 810–822.

    Google Scholar 

  13. J. Sun, K. Wee and J. Zhu, An interior point method for solving a class of stochastic programming problems, in: Nonsmooth Optimization, eds. D. Du, L. Qi and R.Womersley (World Scientific, 1995) pp. 392-404.

  14. J. Sun and G. Zhao, Global linear and local quadratic convergence of a long-step adaptive-mode interior point method for some monotone variational inequality problems, SIAM Journal on Optimization 8 (1998) 123–139.

    Google Scholar 

  15. J. Sun, J. Zhu and G. Zhao, A predictor-corrector algorithm for a class of nonlinear saddle point problems, SIAM Journal on Control and Optimization 35 (1997) 532–551.

    Google Scholar 

  16. S.J. Wright, Stable parallel algorithms for two-point boundary value problems, SIAM J. Sci. Statist. Comput. 13 (1992) 742–762.

    Google Scholar 

  17. S.J. Wright, A collection of problems for which Gaussian elimination with partial pivoting is unstable SIAM J. Sci. Statist. Comput. 14 (1993) 231–238.

    Google Scholar 

  18. Y. Ye and K. Anstreicher, On quadratic and O( \(\sqrt n L\) nL) convergence of a predictor-corrector algorithm for LCP, Mathematical Programming 62 (1993) 537–552.

    Google Scholar 

  19. C. Zhu, Solving large-scale minimax problems with the primal-dual steepest descent algorithm, Mathematical Programming 67 (1994) 53–76.

    Google Scholar 

  20. J. Zhu, A path-following algorithm for a class of convex programming problems, Zeitschrift für Operations Research 36 (1992) 359–377.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hegland, M., Osborne, M. & Sun, J. Parallel Interior Point Schemes for Solving Multistage Convex Programming. Annals of Operations Research 108, 75–85 (2001). https://doi.org/10.1023/A:1016098709653

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1016098709653

Navigation