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A provisioning problem with stochastic payments

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  • Pagnoncelli, Bernardo K.
  • Vanduffel, Steven

Abstract

We consider the problem of determining the minimal requirement one must establish in order to meet a series of future random payments. It is shown in a very general setting that this problem can be recast as a chance constrained model and how the technique of Sample Average Approximation can be employed to find solutions. We also use comonotonic theory to analyze analytical approximations in a restricted Gaussian setting. Our numerical illustrations demonstrate that the Sample Average Approximation is a viable and efficient way to solve the stated problem generally and outperforms the analytical approximations. In passing we present a result that is related to Stein’s famous lemma (Stein, 1981) and is of interest in itself.

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  • Pagnoncelli, Bernardo K. & Vanduffel, Steven, 2012. "A provisioning problem with stochastic payments," European Journal of Operational Research, Elsevier, vol. 221(2), pages 445-453.
    • Handle: RePEc:eee:ejores:v:221:y:2012:i:2:p:445-453
    DOI: 10.1016/j.ejor.2012.01.065
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    Cited by:

    1. Carole Bernard & Ludger Rüschendorf & Steven Vanduffel, 2017. "Value-at-Risk Bounds With Variance Constraints," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(3), pages 923-959, September.
    2. Tsai, Shing Chih & Zheng, Ya-Xin, 2013. "A simulation optimization approach for a two-echelon inventory system with service level constraints," European Journal of Operational Research, Elsevier, vol. 229(2), pages 364-374.
    3. Xu, Liang & Gao, Chunyan & Kou, Gang & Liu, Qinjun, 2017. "Comonotonic approximation to periodic investment problems under stochastic drift," European Journal of Operational Research, Elsevier, vol. 262(1), pages 251-261.

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