Weighted sum of objectives |
This option means that the approximate Pareto points found within each sub-optimization will be sorted and selected based on the value of the combined objective function. |
Desired levels of objectives |
This option means that the approximate Pareto points found within each sub-optimization will be sorted and selected based on the Chebyshev distance from the desired levels of all objectives. You can enter the designed levels for all your objective parameters using the Configure desired levels list. These levels create an imaginary nadir point for the algorithm that selects the Pareto points. The desired levels should be set sufficiently far away from the achievable levels of output parameters. |
One point only with the best selected criterion value |
If this option is selected, only one best approximate Pareto point will be analyzed and added to the internal approximation data set. |
A specified number of best Pareto points |
If this option is selected, you can enter a specific value for the number of approximate Pareto points to be analyzed and added to the interal approximation data set. |
A percentage of the entire Pareto set (1...100%) |
If this option is selected, you can enter a percentage value that will control how many approximate Pareto points are analyzed and added to the internal approximation data set. In addition, you can select the Maximum number of points for the approximate Pareto set. |