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An Automation System for Optimizing a Supply Chain Network Design under the Influence of Demand Uncertainty

Abstract

This research develops and applies an integrated hierarchical framework for modeling a multi-echelon supply chain network design, under the influence of demand uncertainty. The framework is a layered integration of two levels: macro, high-level scenario planning combined with micro, low-level Monte Carlo simulation of uncertainties in demand. To facilitate rapid simulation of the effects of demand uncertainty, the integrated framework was implemented as a dashboard automation system using Microsoft Excel, Risk Solver, and Visual Basic. The integrated framework has been applied to the problem of quantifying the effects of demand uncertainty on total cost in multi-echelon supply chain network design for high-tech products.

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