Many
supply chain problems are involved with
uncertainty in several
input parameters where even the distributions of the stochastic
parameters are unknown. In this paper, we introduce a mathematical
model which incorporates demand and supply with uncertainties for
assembly lines with different products. In some cases, assembly
lines may use the same raw material or assembly parts which could
end up having both shortage and inventory expenditures,
simultaneously. In many realistic cases, the supply chain model has
many input parameters with uncertainty. The primary objective of
this model is to determine the supply chain cost when the
perturbation of the parameters is under consideration. The proposed
model of this paper is solved by using the recent advances of Robust
Optimization Techniques. The implementation of the proposed method
is shown using some numerical example and the results are compared
with Monte Carlo simulation.
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