Hello,
When using a gradient driven optimization (I am currently using LD_MMA
and LD_SLSQP), is it a requirement that the start value of the
optimisation satisfies the inequality constraints?
I currently observe that, if I initialise optimisation with an x which
is "outside" the constraint area, the optimization seems to "jump" out
of constraint mode (no calls at all to the constraint functions) and
just solves the problem as if it was unconstrained.
My objective function is a quadratic form, and my constraints are
non-linear and non-convex.
There is still the possibility that my gradients are wrong, but I would
just like to sort this concern with the start value out, before digging
deeper into my math (my brain hurts already)!
Thanks!
Julius
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