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Two-stage stochastic mixed-integer linear programming: The conditional scenario approach

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  • Beltran-Royo, C.

Abstract

In this paper we consider the two-stage stochastic mixed-integer linear programming problem with recourse, which we call the RP problem. A common way to approximate the RP problem, which is usually formulated in terms of scenarios, is to formulate the so-called Expected Value (EV) problem, which only considers the expectation of the random parameters of the RP problem. In this paper we introduce the Conditional Scenario (CS) problem which represents a midpoint between the RP and the EV problems regarding computational tractability and ability to deal with uncertainty. In the theoretical section we have analyzed some useful bounds related to the RP, EV and CS problems. In the numerical example here presented, the CS problem has outperformed both the EV problem in terms of solution quality, and the RP problem with the same number of scenarios as in the CS problem, in terms of solution time.

Suggested Citation

  • Beltran-Royo, C., 2017. "Two-stage stochastic mixed-integer linear programming: The conditional scenario approach," Omega, Elsevier, vol. 70(C), pages 31-42.
  • Handle: RePEc:eee:jomega:v:70:y:2017:i:c:p:31-42
    DOI: 10.1016/j.omega.2016.08.010
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    1. Parisio, Alessandra & Neil Jones, Colin, 2015. "A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand," Omega, Elsevier, vol. 53(C), pages 97-103.
    2. Alonso-Ayuso, A. & Escudero, L. F. & Garín, A. & Ortuño, M. T. & Pérez, G., 2005. "On the product selection and plant dimensioning problem under uncertainty," Omega, Elsevier, vol. 33(4), pages 307-318, August.
    3. Peter Kall & János Mayer, 2005. "Stochastic Linear Programming," International Series in Operations Research and Management Science, Springer, number 978-0-387-24440-2, December.
    4. Paul H. Zipkin, 1980. "Bounds on the Effect of Aggregating Variables in Linear Programs," Operations Research, INFORMS, vol. 28(2), pages 403-418, April.
    5. Åsa Hallefjord & Sverre Storøy, 1990. "Aggregation and Disaggregation in Integer Programming Problems," Operations Research, INFORMS, vol. 38(4), pages 619-623, August.
    6. S. E. Wright, 1994. "Primal-Dual Aggregation and Disaggregation for Stochastic Linear Programs," Mathematics of Operations Research, INFORMS, vol. 19(4), pages 893-908, November.
    7. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    8. Georg Ch. Pflug & Alois Pichler, 2011. "Approximations for Probability Distributions and Stochastic Optimization Problems," International Series in Operations Research & Management Science, in: Marida Bertocchi & Giorgio Consigli & Michael A. H. Dempster (ed.), Stochastic Optimization Methods in Finance and Energy, edition 1, chapter 0, pages 343-387, Springer.
    9. Albareda-Sambola, Maria & Fernández, Elena & Saldanha-da-Gama, Francisco, 2011. "The facility location problem with Bernoulli demands," Omega, Elsevier, vol. 39(3), pages 335-345, June.
    10. Nickel, Stefan & Saldanha-da-Gama, Francisco & Ziegler, Hans-Peter, 2012. "A multi-stage stochastic supply network design problem with financial decisions and risk management," Omega, Elsevier, vol. 40(5), pages 511-524.
    11. Alonso-Ayuso, Antonio & Escudero, Laureano F. & Teresa Ortuno, M., 2003. "BFC, A branch-and-fix coordination algorithmic framework for solving some types of stochastic pure and mixed 0-1 programs," European Journal of Operational Research, Elsevier, vol. 151(3), pages 503-519, December.
    12. Paul H. Zipkin, 1980. "Bounds for Row-Aggregation in Linear Programming," Operations Research, INFORMS, vol. 28(4), pages 903-916, August.
    13. Samer Takriti & John R. Birge, 2000. "Lagrangian Solution Techniques and Bounds for Loosely Coupled Mixed-Integer Stochastic Programs," Operations Research, INFORMS, vol. 48(1), pages 91-98, February.
    14. David F. Rogers & Robert D. Plante & Richard T. Wong & James R. Evans, 1991. "Aggregation and Disaggregation Techniques and Methodology in Optimization," Operations Research, INFORMS, vol. 39(4), pages 553-582, August.
    15. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
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