The Monte Carlo Simulation Process

The simulation process includes data collection, random-number assignment, model formulation, and analysis. This process is known as Monte Carlo simulation, after the European gambling capital, because of the random numbers used to generate the simulation events.

Data Collection

Simulation requires extensive data gathering on costs, productivities, capacities, and probability distributions. Typically, one of two approaches to data collection is used. Statistical sampling procedures are used when the data are not readily available from published sources or when the cost of searching for and collecting the data ...

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