Inventory models under uncertainty: an adaptive approach

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.

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Year of publication:	1986
Authors:	Rubinstein, Y.R. ; Kreimer, J.
Published in:	Mathematics and Computers in Simulation (MATCOM). - Elsevier, ISSN 0378-4754. - Vol. 28.1986, 3, p. 169-188
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011050785