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Monte Carlo methods are widely used in the fields of finance, engineering, supply chain, and science to model phenomena with significant uncertainty in their inputs.
Monte Carlo is a mathematical technique used to model the probability of different outcomes in a process that cannot be easily predicted due to the intervention of random variables. It is a powerful tool for understanding the impact of risk and uncertainty in various fields. This method relies on repeated random sampling to simulate the behaviour of complex systems and processes.
The problem is modelled by a probability distribution for each variable that has inherent uncertainty. Large numbers of random samples are drawn from these probability distributions, and these samples are used to compute the outcomes. This process is repeated many times to create a distribution of possible outcomes, which can be analysed statistically to provide predictions of how a system is likely to behave.
Monte Carlo simulation is accomplished in a several step process, being:-
- Define how each variable can vary using probability distributions.
- Randomly select values for these variables based on their distributions.
- Use these randomly selected values to simulate the system’s…
