Except where indicated, this example uses the recommended Crystal Ball run preferences. See Setting Crystal Ball Run Preferences. |
With Hotel Design.xls open in Crystal Ball:
As you click Next to step through the problem, note:
To ensure that the probability of demand exceeding capacity does not exceed 20%, the projected number of rooms sold (cell H12) is a forecast in the Crystal Ball model, with a requirement added in the Objectives panel. Specifically, the total room demand is limited by a requirement using the forecast statistic Percentile (80), with an upper bound of 450.
This problem has three decision variables and no constraints.
On the Options panel, click Advanced Options and select Automatically stop after 500 non-improving solutions.
The results appear in Figure 36, Hotel pricing model optimization results. The mean of total revenue is $40,406.61 and room prices are $110 for Gold, $133 for Platinum, and $80.00 for Standard.
The Crystal Ball simulation of this solution in Figure 37, Hotel pricing solution (percentiles view) verifies that the chance of demand exceeding capacity is just slightly less than 20% (100% – 80.81%).
