To follow this example:
Open Portfolio Revisited.xls in Crystal Ball.
This example uses the Crystal Ball run preferences recommended in Setting Crystal Ball Run Preferences.
Start the OptQuest wizard.
As you click Next to step through the problem, note:
The objective refers to the new multi-objective function: Maximize the Final Value of Mean minus stdev. The statistic to optimize is Final Value, to calculate only the statistical values for the total expected return forecast at the end of the simulation. There are no requirements.
The decision variables and constraints are the same as previous Portfolio Allocation examples.
On the Options panel, select Run for 2000 simulations, and then click Advanced Options and select Automatically stop after 500 non-improving solutions.
Run the optimization for 2000 simulations.
The results appear in Figure 51, Portfolio Revisited Multi-objective Optimization Results. Mean minus std dev is maximized at $3052.33 and fund values are as follows:
Aggressive Growth = $16,400
Growth and Income = $8,600
Income = $25,000
Money Market = $50,000
After reviewing the results, close Portfolio Revisited.xls without saving it.
Tip: | Multi-objective optimization is especially useful when it is difficult to determine reasonable lower or upper bounds for requirement statistics. This method is also recommended for situations where OptQuest has trouble finding feasible solutions that satisfy many requirements. Using a single objective with requirements is generally easier to implement and understand. |