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Influence Diagrams with Continuous Decision Variables and Non-Gaussian Uncertainties

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  • Barry R. Cobb

    (Department of Economics and Business, Virginia Military Institute, Lexington, Virginia 24450)

Abstract

The continuous decision MTE influence diagram (CDMTEID) uses mixtures of truncated exponentials (MTE) potentials to approximate probability density functions (pdfs) and utility functions, and develops a piecewise-linear decision rule for continuous decision variables. The operations for solving CDMTEIDs are defined, and the abilities of this model to identify nonmonotonic decision rules and accommodate discrete variables with continuous parents are demonstrated. The CDMTEID solution to a problem with a continuous decision variable and a non-Gaussian continuous chance variable is presented and compared to a benchmark solution and existing models. The CDMTEID improves the quality of the decision rule and the value of information, as compared to other methods for the example problem.

Suggested Citation

  • Barry R. Cobb, 2007. "Influence Diagrams with Continuous Decision Variables and Non-Gaussian Uncertainties," Decision Analysis, INFORMS, vol. 4(3), pages 136-155, September.
    • Handle: RePEc:inm:ordeca:v:4:y:2007:i:3:p:136-155
    DOI: 10.1287/deca.1070.0095
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    References listed on IDEAS

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    Cited by:

    1. L. Robin Keller & Ali Abbas & Manel Baucells & Vicki M. Bier & David Budescu & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Ahti Salo & George Wu, 2010. "From the Editors..," Decision Analysis, INFORMS, vol. 7(4), pages 327-330, December.
      • L. Robin Keller & Manel Baucells & Kevin F. McCardle & Gregory S. Parnell & Ahti Salo, 2007. "From the Editors..," Decision Analysis, INFORMS, vol. 4(4), pages 173-175, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2008. "From the Editors..," Decision Analysis, INFORMS, vol. 5(4), pages 173-176, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2009. "From the Editors ..," Decision Analysis, INFORMS, vol. 6(4), pages 199-201, December.
    2. L. Robin Keller, 2012. "From the Editor---Decisions over Time (Exploding Offers or Purchase Regret), in Game Settings (Embedded Nash Bargaining or Adversarial Games), and in Influence Diagrams," Decision Analysis, INFORMS, vol. 9(1), pages 1-5, March.
    3. Bielza, Concha & Gómez, Manuel & Shenoy, Prakash P., 2011. "A review of representation issues and modeling challenges with influence diagrams," Omega, Elsevier, vol. 39(3), pages 227-241, June.
    4. Chang, Suk-Gwon, 2015. "A structured scenario approach to multi-screen ecosystem forecasting in Korean communications market," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 1-20.
    5. L. Robin Keller, 2009. "From the Editor..," Decision Analysis, INFORMS, vol. 6(3), pages 121-123, September.
    6. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.
    7. Yijing Li & Prakash P. Shenoy, 2012. "A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions," Decision Analysis, INFORMS, vol. 9(1), pages 55-75, March.
    8. Cobb, Barry R. & Johnson, Alan W. & Rumí, Rafael & Salmerón, Antonio, 2015. "Accurate lead time demand modeling and optimal inventory policies in continuous review systems," International Journal of Production Economics, Elsevier, vol. 163(C), pages 124-136.

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