Another partial solution is to use a metametric that combines many different metrics in a non-linear fashion. So for example, if you have three metrics of what you want to maximize, say X,Y, Z, then looking at XYZ is more likely to work well. The key of using the product here rather than a linear sum is that it prevents one from having most efficient solutions where two of the metrics are tiny and one is very large. Polynomial arguments of existing metrics, if properly constructed, can be much more effective than those which don’t. There have been some attempts with genetic algorithms to use this sort of thing to prevent bad optimization in those contexts, but I don’t know any of the details.
Another partial solution is to use a metametric that combines many different metrics in a non-linear fashion. So for example, if you have three metrics of what you want to maximize, say X,Y, Z, then looking at XYZ is more likely to work well. The key of using the product here rather than a linear sum is that it prevents one from having most efficient solutions where two of the metrics are tiny and one is very large. Polynomial arguments of existing metrics, if properly constructed, can be much more effective than those which don’t. There have been some attempts with genetic algorithms to use this sort of thing to prevent bad optimization in those contexts, but I don’t know any of the details.