In the previous lesson, we formulated and analyzed various models on real-life problems. All the models were used with mathematical techniques to have analytical solutions. In certain cases, it might not be possible to formulate the entire problem or solve it through mathematical models. In such cases, simulations proves to be the most suitable method, which offers a near-optimal solution. Simulation is a reflection of a real system, representing the characteristics and behaviour within a given set of conditions.
In simulation, the problem must be defined first. Secondly, the variables of the model are introduced with logical relationship among them. Then a suitable model is constructed. After developing a desired model, each alternative is evaluated by generating a series of values of the random variable, and the behaviour of the system is observed.
Simulation technique is considered as a valuable tool because of its wide area of application. It can be used to solve and analyze large and complex real world problems. Simulation provides solutions to various problems in functional areas like production, marketing, finance, human resource, etc., and is useful in policy decisions through corporate planning models. Simulation experiments generate large amounts of data and information using a small sample data, which considerably reduces the amount of cost and time involved in the exercise.
For example, if a study has to be carried out to determine the arrival rate of customers at a ticket booking counter, the data can be generated within a short span of time can be used with the help of a computer.