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Advantages of using simulation modeling

  • Simulation can be used even in more complex situations:
  1. When the random input variable (r) did not follow a normal distribution, but some other complicated distribution
  2. When the Output variable (S1) is a more complex function of the input variable (r) (unlike a simple equation stated earlier)
  3. If there are multiple input random variables (r1, r2… rn), the simulation approach can predict the probability distribution of the output, resulting from compounding probability distributions of these multiple random variables.
  4. Simulation approach also takes into account the correlations between the various random variables (ρ12, ρ13, ρn1… etc) , by generating joint scenarios for realizations of input variables (no need for complex mathematics)
  5. Simulation is a low cost tool for evaluating strategies. Can be used, to analyze the effect of changing a strategy on the output variable (under the same set of scnearios).

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