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Two-resource stochastic capacity planning employing a Bayesian methodology

Author

Listed:
  • E Stavrulaki

    (Bentley College)

  • D K H Fong

    (Penn State University, University Park)

  • D K J Lin

    (Penn State University, University Park)

Abstract

We examine a stochastic capacity-planning problem with two resources that can satisfy demand for two services. One of the resources can only satisfy demand for a specific service, whereas the other resource can provide both services. We formulate the problem of choosing the capacity levels of each resource to maximize expected profits. In addition, we provide analytic, easy-to-interpret optimal solutions, as well as perform a comparative statics analysis. As applying the optimal solutions effectively requires good estimates of the unknown demand parameters, we also examine Bayesian estimates of the demand parameters derived via a class of conjugate priors. We compare the optimal expected profits when demands for the two services follow independent distributions with informative and non-informative priors, and demonstrate that using good informative priors on demand can significantly improve performance.

Suggested Citation

  • E Stavrulaki & D K H Fong & D K J Lin, 2003. "Two-resource stochastic capacity planning employing a Bayesian methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(11), pages 1198-1208, November.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:11:d:10.1057_palgrave.jors.2601607
    DOI: 10.1057/palgrave.jors.2601607
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    References listed on IDEAS

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    Cited by:

    1. R J Ormerod, 2010. "Rational inference: deductive, inductive and probabilistic thinking," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(8), pages 1207-1223, August.
    2. Stavrulaki, Euthemia, 2011. "Inventory decisions for substitutable products with stock-dependent demand," International Journal of Production Economics, Elsevier, vol. 129(1), pages 65-78, January.

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