Simulation in Decision
© Copyright 2009 Herbert J.
Simulation plays an important role in decision making. In a simulation we use
a computer to calculate trial inputs and resulting outputs to explore alternatives
in the computer before facing them in reality.
- Models for Inputs:
- Deterministic input or outputs from earlier decisions
- Random inputs
- Must follow appropriate distributions
Need to know cumulative
distribution function (P(X≤x);
- Test by the Chi-squared goodness
of fit test
- Want uncorrelated numbers
- In Excel, the function RAND() gives a uniformly distributed random
number real between 0 and 1, not including 1.
- In Excel, the function RANDBETWEEN(LOW,HIGH) returns a uniformly
distributed random integer between LOW and HIGH, inclusive.
- In recent versions of Excel, NORMINV(RAND(), mean, standard_dev)
returns a normally distributed random number, but in older versions of Excel
you need to use the Box-Muller method
(but you need to make both RAND() calls come from one cell). See
- Procesing inputs to outputs
- The real decision problem is modelled by equations that depend on
- Usually done as a simulation table of intermediate values and outputs
with a trail in each row (or group of rows)
- Important to record a trial number (run number), each input value
and the equations used as well as the outputs
- Analysing output
- For each output, compute means, standard deviations, 5% and 95% values
- Graphical views (histograms, line graphs, trend lines)