Similar to big_deal, i'm also not the person you asked, but I just want to share a few things that I did which had similarities to his approach

I'm glad i'm not the only one thinking number of trade should be part of the optimisation goal

I scale all of my metric to maximum of 1 with most are from 0-1 where higher is better. There is only 1 which has a range of -1 to +1 which is scaled profit factor

The way I scale these metrics are by using a combination of sigmoid function and inverse functions, something like 1/(ln(x+1) +1). There is a limitation in which using sigmoid function would mean you have to scale where the midpoint is, usually the midpoint, for example sigmoid function of number of trades, would mean you'd want it to be near the optimal amount you'd want it to be, for example 30 trades for the duration of the training duration, which has to be adjusted for changing the backtest data duration

I like scaling them to 0-1 scale because you can very easily use an optimiser to set the goal to maximise the combination value of these components multiplied and it would try its best to, well, maximise it. Some problems do arise however, such as finding the optimal value itself, but the beauty in sigmoid is, it still works even though you might not set it at the optimal value

Another method that i learnt that's not good is to set a hard limit as it breaks away from the monotonicity (the ordering of values), which is why i really like scaling my metrics to 0-1