When hovering the cursor over any of the dots in the Optimizer Result window’s scatter plot, GC displays the set of objectives for the corresponding solution. Clicking on the dot will push the corresponding parameters into the parametric model and thus instantiate the solution in the geometric model.
When exploring the Optimizer results, users need to consider that genetic algorithms attempt to find solutions that are satisfying all objectives. Therefore, they often do not find the extremes in the solution space but explore the areas where trade-offs are more intense, the middle-ground where many or most objectives are satisfied to some degree.
Example of a multi-objective optimization with three objectives: solving for all planar panels, solving for maximum ventilation openings, and solving for avoiding extreme peaks in the roof. Shown are four dots in the scatter plot ranging from maximum vent opening and minimum planarity to minimum vent opening and maximum planarity.
Any such invoked parameter setting can be saved as a transaction in order to preserve specific instances for later access and closer inspection/evaluation or as basis for further design.