Inventory models under uncertainty: an adaptive approach

Y.R. Rubinstein and J. Kreimer

Mathematics and Computers in Simulation (MATCOM), 1986, vol. 28, issue 3, 169-188

Abstract: Consider the following nonlinear programming (NLP) problem: minxg0(x)=minx∫ψ(x, y)fY(y, x) dy=min E[ψ0(x, Y)]s.t.gj(x)=∫ψj(x, y)ƒY(x, y) dy=E[ψj(x, Y)] ⩽ 0, j=1,…,M,where x ∈ X ⊂ Rn,y∈ D ⊂ Rm, ψj(x,Y), j=0,1,…,M are given functions, and fT(y, x)is a probability density function depending on a vector of parameters x.

Date: 1986
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:28:y:1986:i:3:p:169-188

DOI: 10.1016/0378-4754(86)90025-X

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