Problem in Adjoint based Optimization
 

Hello All,

I use the SLSQP method for an optimization problem having 1 objective with 1 constraint and 200 control points. As usual, at the first design (DSN001), it computes adjoints. After that, it only computes DIRECT solutions till 12th iteration. It looks like that there is no need to wait until 12th iteration, because it goes far from global min iteration by iteration. After 12th iteration it does not compute gradients until 23rd iteration similarly. I want to shorten this number if there is an option in SU2.

I also checked the Fortran script that probably SU2 uses (https://github.com/scipy/scipy/blob/.../slsqp_optmz.f)
In that script, line 454 give some idea about why it is like that. But I couldn't be sure.

I really appreciate, if you could help me.

Omur