Is it not possible to implement a simple least squares objective function in Optislang? 
J(p) = zWz     or after linearisation    (GWG)p = GWz
 z = resiude vector
W = weighting matrix
G = weighting matrix (partial derivative of the residuals after the paramers)
p = parameter change
I would like to know if it is possible to implement a least squares objective function using Optislang, or if there are simpler approaches that can take my weighting matrices directly from Optislang. Furthermore, I would be interested to know which approach is considered the best or simplest to realise the alignment between test and simulation. Are there any proven methods that are particularly recommended and what factors should be taken into account when choosing?