On Jun 28, 2012, at 3:16 AM, Matt Peddie wrote:
Would the new MMA-like algorithm support nonlinear equality constraints?
No.
I'm not looking for something that can take a Hessian just so I can have the fun of passing it one; since automatic differentiation gives me theHessian without any extra work on my part, I wondered whether I could easily put it to use. SLSQP will probably do fine as it is.
Just because automatic differentiation gives you the Hessian doesn't mean that it is free (in terms of computer time). Computation of gradients by adjoint methods (or automatic differentiation in "reverse" mode) is comprable in cost to computing the objective function, but my understanding is that the computation of the Hessian in general scales like the objective function multiplied by the number of degrees of freedom.
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