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Bounds on stochastic convex allocation problems

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  • Chanaka Edirisinghe
  • Derek Atkins
  • Paul Iyogun

Abstract

We consider a stochastic convex program arising in a certain resource allocation problem. The uncertainty is in the demand for a resource which is to be allocated among several competing activities under convex inventory holding and shortage costs. The problem is cast as a two–period stochastic convex program and we derive tight upper and lower bounds to the problem using marginal distributions of the demands, which may be stochastically dependent. It turns out that these bounds are tighter than the usual bounds in the literature which are based on limited moment information of the underlying random variables. Numerical examples illustrate the bounds.

Suggested Citation

  • Chanaka Edirisinghe & Derek Atkins & Paul Iyogun, 1994. "Bounds on stochastic convex allocation problems," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 10(2), pages 123-140.
    • Handle: RePEc:wly:apsmda:v:10:y:1994:i:2:p:123-140
    DOI: 10.1002/asm.3150100206
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    Cited by:

    1. Edirisinghe, Chanaka & Atkins, Derek, 2017. "Lower bounding inventory allocations for risk pooling in two-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 187(C), pages 159-167.

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