Then 2) Every time step where you test, you start by choosing one of the correlates at random, and then use that one to measure production.

This is almost equivalent to having a linear function where you add the three metrics together. (It's worse because it adds noise instead of averaging out noise.) Do you think adding the three together makes for a good metric, or might an optimization of that function fail because it makes crazy tradeoffs on an unconsidered dimension?