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What is a Monte Carlo simulation primarily based on?
A subset of digital simulation models based on random processes
A deterministic model of project management
A static analysis of historical data
An algorithm for optimizing supply chain logistics
The correct answer is: A subset of digital simulation models based on random processes
A Monte Carlo simulation primarily relies on the use of random processes to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. By running simulations many times, each with a set of randomly generated inputs, the Monte Carlo method generates a distribution of possible results based on varying scenarios. This method is especially useful in supply chain management and project management, where uncertainty and variability are inherent. By allowing for the incorporation of risk into quantitative analyses, Monte Carlo simulations can aid decision-makers by providing insight into the likelihood of success or failure under various conditions. The other options do not accurately capture the essence of what a Monte Carlo simulation is. A deterministic model focuses on precise outcomes with no randomness involved, while a static analysis of historical data does not incorporate the stochastic nature of future events. Similarly, an algorithm for optimizing logistics typically involves specific mathematical techniques rather than the broad probabilistic framework inherent to Monte Carlo simulations.