Logical Decisions - Classweb

pass, LDW replaces each probabilistic level with a single number
that is sampled from the probability distribution for the level. A
sample is a number that is randomly drawn from a probability
distribution with a likelihood that is based on the probability
distribution.
For example, if a level with units of horsepower has a discrete
distribution of p(150hp) = 0.5, p(160hp) = 0.3, and p(170hp = 0.2),
then about 50% of the samples will have a level of 150hp, about
30% of them will have a level of 160hp and about 20% of them will
have a level of 170hp.
Because the samples are based on random numbers, the
proportions won't exactly match the fractions in the probability
distribution. However after a large number of samples have been
taken the proportions should be very close.
After each probabilistic level has been sampled, LDW computes
the alternative’s utility and saves it. After many passes, you will
get an idea of the probability distribution of the alternative’s
utility.
The following LDW options use Monte Carlo simulations:
! the Options::Simulation Options option lets you define
the number of samples to use when doing a Monte
Carlo simulation.
! the Results::Alternative Uncertainty Graph option lets
you see a histogram and cumulative probability
distribution for any alternative and measure or
goal.
! the Results::Uncertainty Summary option lets you
generate a table comparing the uncertainties for all
the alternatives for any measure or goal.
! the Results::Rank Alternatives option has a feature that
lets you show the uncertainty range for each
alternative along with its expected utility.
Adding Comments to Levels. The probability dialog box shown
in Figure 6-10 includes an edit box for entering comments. You
can use this comment field for any level, regardless of whether the
level is probabilistic. This comment field lets you add a comment
6-28 Section 6 -- Using LDW 1: Structuring