When analyzing a case study about supply chain optimization, which sophisticated model is best suited for handling uncertainties and complexities?
- Decision Trees
- K-Means Clustering
- Linear Programming
- Monte Carlo Simulation
In supply chain optimization, where uncertainties and complexities are common, the Monte Carlo Simulation model is effective. It helps simulate various possible scenarios and their outcomes, allowing for better decision-making in the face of uncertainties.
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