I have some thoughts, in no particular order:

* The first article does not talk about monte carlo at all, from what I can tell.
* I wouldn't know what the "best" optimization method is, I simply use the most practical ones. Currently, this would be the default Zorro optimization method.
* Perhaps the method described in the second article can be a useful technique, it might be worthy of experimentation.
* One other optimization method I like is described in Trading Systems by Jaekle and Tomasini. When they initially design a trading system, they use a dual-parameter brute force optimization to produce various 3D plots, in order to identify stable profitable parameter regions. This helps with the final design of the script. I have been able to produce such 3D plots by exporting trade data CSV's and making 3d plots with the plotly R package. (Anyways, this has nothing to do with statistics.)