Simulation - 2 Simulation of Demand

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Simulation

Monte Carlo Method:
The ‘Monte Carlo’ simulation technique involves conducting repetitive experiments on the model of the system under study, with some known probability distribution to draw random samples (observations) using random numbers. If a system cannot be described by a standard probability distribution such as normal, Poisson, exponential, etc, an empirical probability distribution can be constructed. The Monte Carlo simulation technique consists of the following steps:
(1) Setting up a probability distribution for variables to be analyzed.
(2) Building a cumulative probability distribution for each random variable.
(3) Generating random numbers and then assigning an appropriate set of random numbers to represent value or range (interval) of values for each random variable.
(4) Conducting the simulation experiment using random sampling.
(5) Repeating Step – 4 until the required number of simulation runs has been generated.
(6) Designing and implementing a course of action and maintaining control.

Case/Problem:
Demand(in '00
Cakes per day): 0 5 10 15 20 25
No. of Days: 2 11 8 21 5 3

Using the following sequence of random numbers, simulate the demand for the next 10 days and find out the average demand:
35, 52, 90, 13, 23, 73, 74, 57, 35, 83

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