Understanding Monte Carlo Simulation

What is Monte Carlo Simulation

Simulation is one of the most widely used probabilistic modeling tools in industry. It is used for the analysis of existing systems and for the selection of hypothetical systems. There will be
times when the physical system is too complicated for analytical modeling; in such a case, simulation would be an appropriate tool.

For example, suppose a bank has been receiving complaints from customers regarding the length of time that customers are spending in line waiting at the counter. Management has decided to add some extra counters; they now need to decide how many to add. Simulation models can be used to help management in determining the number of counters to add. A computer program would be written to generate randomly arriving customers, and then process each customer. In such a manner, the effect of having different numbers of counters could be determined before the expense of building them is incurred

A simulation could be built to model the same system as the analytical model describes. If the two models agree, the analyst would have confidence in their use. It can also be used to increase understanding of the process being modeled. It is impossible to build a simulation of something not understood, so just the process of developing a simulation of a specific process will force an understanding of that process

Though there are powerful simulation languages, EXCEL has a good number of features to perform simulation