Monte-Carlo helps us to forecast future models depending on range of possible inputs. For instance to complete a project we might have different range of time minimum time, maximum time and estimated time. Monte-carlo simulation runs over these ranges of input values and gives us different possibilities the project can end up to. It can tell you depending on these ranges what are the possible outcomes.
Figure: - Monte-Carlo Applied
In Monte-Carlo simulation random value is selected from the range and possibility / model is generated. This model is saved and then the second random value is selected and so on. For instance consider the below figure ‘Task1 and Task2’. ‘Task2’ can be finished only when ‘Task1’ is completed. We have also chosen the min and max range in which both the task can be completed. ‘Task1’ can be completed in a minimum time of 1 day and maximum of 3 days. ‘Task2’ can be completed in minimum 2 days and in maximum 4 days.
Figure: - Task1 and Task2
Now let’s apply Monte Carlo simulation. Below figure ‘Monet Carlo on Both Tasks’ shows the different combinations.
Figure: - Monte Carlo on Both Tasks
Now let’s collect the number of times the days have occurred. Below figure ‘Number of Possibilities’ shows that 5 days has occurred the most times. There is a high possibility that task1 and task2 will be completed in 5 days.
Figure: - Number of possibilities
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