A certain goal program I've been working on has three goals that each operate at different scales.
Two of the goals stay between 0-10, so any deviation from the goal is generally only a couple of "points" away from the goal.
The third goal has a much larger scale (its a measure of distance travelled), so the deviations from the goal can range from 10s of "points" away to 100s, depending on the solution.
Because of this difference in magnitude of the deviations derived from each goal, the model has an implicit bias towards satisfying the third goal as closely as possible.
I suppose one could normalize all the goals such that they're on the same scale or maybe weight the goals such that the larger magnitude one gets truncated down to be comparable to the others.
Is there a standard practice for dealing with these scale differences in a goal program?