Except where indicated, this example uses the recommended Crystal Ball run preferences. See Setting Crystal Ball Run Preferences. |
To run the optimization:
In Crystal Ball, set the number of trials per simulation to 2000, since tail-end percentile requirements need more accuracy.
As you click Next to step through the problem, notice the following:
The objective is to minimize the mean remediation cost while requiring that the population risk be less than or equal to 1E-4 with 95% certainty.
There are two decision variables: Remediation Method (cell D13), and Cleanup Efficiency (cell D14). You can select Show cell locations to confirm decision variable cells. Notice that the Category type was chosen for Remediation Method since it acts as an “index” variable for selecting one of the methods.
On the Options panel, click Advanced Options and select Automatically stop after 500 non-improving solutions.
The results are shown in Figure 42, Groundwater cleanup optimization results, following. The solution in Figure 42, Groundwater cleanup optimization results minimizes costs at $10,909 while keeping the risk level at 9.99E-5, rounded.
The distributions for the total remediation cost and the population risk are shown in Figure 43, Groundwater cleanup total remediation cost forecast chart and Figure 44, Groundwater cleanup population risk forecast chart.