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Stochastic programming and the option of doing it differently

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  • Stein Wallace

Abstract

Option theory and stochastic programming are tightly linked. Most options can be analyzed in both frameworks, and the two approaches support each other in many slightly more complex situations. But this similarity hides some central differences in perspective. This short note tries to focus on one of these, namely the fact that option theory can be applied only to options already identified, while stochastic programming is able to help us find options in contexts where it is not at all clear what they are, and where finding might be more important than valuing. Copyright Springer Science+Business Media, LLC 2010

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  • Stein Wallace, 2010. "Stochastic programming and the option of doing it differently," Annals of Operations Research, Springer, vol. 177(1), pages 3-8, June.
    • Handle: RePEc:spr:annopr:v:177:y:2010:i:1:p:3-8:10.1007/s10479-009-0600-x
    DOI: 10.1007/s10479-009-0600-x
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    References listed on IDEAS

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    1. Stein W. Wallace, 2000. "Decision Making Under Uncertainty: Is Sensitivity Analysis of Any Use?," Operations Research, INFORMS, vol. 48(1), pages 20-25, February.
    2. Julia L. Higle & Stein W. Wallace, 2003. "Sensitivity Analysis and Uncertainty in Linear Programming," Interfaces, INFORMS, vol. 33(4), pages 53-60, August.
    3. Adam Borison, 2005. "Real Options Analysis: Where Are the Emperor's Clothes?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 17(2), pages 17-31, March.
    4. James E. Smith & Robert F. Nau, 1995. "Valuing Risky Projects: Option Pricing Theory and Decision Analysis," Management Science, INFORMS, vol. 41(5), pages 795-816, May.
    5. Zhao, Yonggan & Ziemba, William T., 2008. "Calculating risk neutral probabilities and optimal portfolio policies in a dynamic investment model with downside risk control," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1525-1540, March.
    6. Arnt-Gunnar Lium & Teodor Gabriel Crainic & Stein W. Wallace, 2009. "A Study of Demand Stochasticity in Service Network Design," Transportation Science, INFORMS, vol. 43(2), pages 144-157, May.
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    Cited by:

    1. Julien Keutchayan & Janosch Ortmann & Walter Rei, 2023. "Problem-driven scenario clustering in stochastic optimization," Computational Management Science, Springer, vol. 20(1), pages 1-33, December.
    2. Sebastian Maier, 2021. "Re-evaluating natural resource investments under uncertainty: An alternative to limited traditional approaches," Annals of Operations Research, Springer, vol. 299(1), pages 907-937, April.
    3. Hui, Yer Van & Gao, Jia & Leung, Lawrence & Wallace, Stein, 2014. "Airfreight forwarder’s shipment planning under uncertainty: A two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 83-102.
    4. Alexandra M. Newman & Martin Weiss, 2013. "A Survey of Linear and Mixed-Integer Optimization Tutorials," INFORMS Transactions on Education, INFORMS, vol. 14(1), pages 26-38, September.
    5. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    6. Vaagen, Hajnalka & Kaut, Michal & Wallace, Stein W., 2017. "The impact of design uncertainty in engineer-to-order project planning," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1098-1109.
    7. Biju Thapalia & Stein Wallace & Michal Kaut & Teodor Crainic, 2012. "Single source single-commodity stochastic network design," Computational Management Science, Springer, vol. 9(1), pages 139-160, February.

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