Monte Carlo simulation
Modeling and simulation tutorial
20201120 01:29:19
Monte Carlo simulation
Monte Carlo simulation is a computerized mathematical technique for generating random samples based on some known distribution for numerical experiments. This method is applied to quantitative risk analysis and decisionmaking problems. This method is used by professionals of different backgrounds such as finance, project management, energy, manufacturing, engineering, research and development, insurance, oil and gas, transport, etc.
This method was first used by scientists working on the atomic bomb in 1940. This method can be used in situations where we have to make an estimate and uncertain decisions such as weather forecasts.
Monte Carlo simulation ─ Important features
Here are the three important features of theMonteCarlo method 
 Its output should generate random samples.
 Its input distribution must be known.
 Its result must be known when performing an experiment.
Monte Carlo simulation ─ Advantages
 Easy to implement.
 Provides statistical sampling for numerical experiments using the computer.
 Provides an approximate solution to math problems.
 Can be used d for stochastic and deterministic problems.
Monte Carlo simulation ─ Disadvantages

Takes time because there is a need to generate a large number of samples to obtain the desired result.

The results of this method are only an approximation of the true values, not the exact.
Monte Carlo simulation method ─ Diagram of flux
The following illustration shows a generalized Monte Carlo simulation flowchart.