[tomp1993]

Hi All,
i am using python SLSQP as an optimiser and asking it to call SU2 V6.2.0 for direct and discrete adjoint solutions, and it is doing a pretty good job of reducing drag but when it gets near an optima the process starts doing endless linesearches with only minute changes in design between each major iteration - yet i know that there is still a better solution than the one found and i am confident that it has not found a local minima.
This happens in both fixed CL mode (not using lift adjoint) and also not fixed CL but constrained lift through lift adjoint and addition of FFD_AOA design variable.
i have tried scaling the function and gradient values (as a means of bypassing the armijo condition) and have tried using ever-smaller values for ftol (an argument given to slsqp) but still get the linesearches.
is there a reliable means of 'switching off' this line searching feature or does anyone have any advice as to what exact criteria the optimiser uses to decide wether or not to do one of these searches?
the lift and drag sensitivities are not zero and not necessarily conflicting when the linesearch starts.
thankyou for any suggestions!
Tom