Skip to main content
Log in

Designing a majorization scheme for the recourse function in two-stage stochastic linear programming

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

Abstract

We discuss issues pertaining to the domination from above of the second-stage recourse function of a stochastic linear program and we present a scheme to majorize this function using a simpler sublinear function. This majorization is constructed using special geometrical attributes of the recourse function. The result is a proper, simplicial function with a simple characterization which is well-suited for calculations of its expectation as required in the computation of stochastic programs. Experiments indicate that the majorizing function is well-behaved and stable.

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. J.R. Birge and J.H. Dulá, “Bounding separable recourse functions with limited distribution information,” Annals of Operations Res. 30 (1991), 277–298.

    Google Scholar 

  2. J.R. Birge and S.W. Wallace, “A separable piecewise linear upper bound for stochastic linear programs,” SIAM J. Control and Optimization 26(3) (1988), 725–739.

    Google Scholar 

  3. J.R. Birge and R.J.-B. Wets, “Designing approximation schemes for stochastic optimization problems, in particular for stochastic programs with recourse,” Mathematical Programming Study 27 (1986), 54–102.

    Google Scholar 

  4. J.R. Birge and R.J.-B. Wets “On-line solution of linear programs using sublinear functions,” Technical Report No. 86-25, IOE Dept., The University of Michigan, Ann Arbor, MI.

  5. J.R. Birge and R.J.-B. Wets, “Sublinear upper bounds for stochastic linear programs with recourse,” Mathematical Programming 43 (1989), 131–149.

    Google Scholar 

  6. J.H. Dulá, “Geometry of optimal value functions with applications to redundancy in linear programming,” J. of Optimization Theory and Applications 81(1) (1994).

  7. J.H. Dulá, “An upper bound on the expectation of simplicial functions of multivariate random variables,” Math. Programming 55 (1992), 69–80.

    Google Scholar 

  8. J.H. Dulá and R.V. Murthy, “A second order upper bound on the expectation of sublinear polyhedral functions,” Operations Res. 40(5) (1992).

  9. N.C.P. Edirisinghe and W.T. Ziemba, “Bounds for two-stage stochastic programs with fixed recourse,” Mathematics of Operations Research (1993), to appear.

  10. P. Kall and E. Keller, “GENSLP: A program for generating input for stochastic linear programs with complete fixed recourse,” Manuscript, Institüt fur Operations Research der Universität Zürich, Zürich CH-8006, Switzerland, 1985.

    Google Scholar 

  11. P. Kall, A. Ruszczynski, and K. Frauendorfer, “Approximations in stochastic programming,” in Numerical Techniques for Stochastic Optimization, Ermoliev and Wets, eds., Springer-Verlag, Berlin, 1988.

    Google Scholar 

  12. A. Prékopa and R.J.-B. Wets, “Stochastic Programming 84,” Mathematical Programming Study, 27 (1986).

  13. R.T. Rockafellar, Convex Analysis, Princeton University Press, Princeton, NJ, 1970.

    Google Scholar 

  14. D.W. Walkup and R.J.-B. Wets, “Stochastic programs with recourse,” SIAM J. Applied Math., 15 (5) (1967), 1299–1314.

    Google Scholar 

  15. S.W. Wallace, “A piecewise linear upper bound on the network recourse function,” Math. Programming, 38, (1987), 133–146.

    Google Scholar 

  16. S.W. Wallace and R.J.-B. Wets, “Preprocessing in stochastic programming: the case of linear programs,” ORSA Journal on Computing, 4(1) (1992).

  17. R.J.-B. Wets. and C. Witzgall, “Algorithms for frames and lineality spaces of cones,” J. of Res. of the Nat. Bureau of Standards — B Math. and Math. Physics, 71B(1) (1967), 1–7.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dulá, J.H. Designing a majorization scheme for the recourse function in two-stage stochastic linear programming. Comput Optim Applic 1, 399–414 (1993). https://doi.org/10.1007/BF00248764

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00248764

Keywords

Navigation