For quadratic problems you really should use quadprog.
You can also try the 'parma' package which provides a nice interface to
frame your problem and constraints and then solve it using either an LP,
QP, NLP (with analytic derivatives) or GNLP formulation (depending on
the intersection of problem and constraint type).
Regards,
Alexios
On 06/06/2013 08:58, Dominykas Grigonis wrote:
ROI::ROI_solve( problem, solver, control, ... )
DEoptim::DEoptim() # differential evolution!
Rsolnp # general non-linear optimisation
This is from my R conspects. Can try to take a look at those.
For your problem quadprog might be the best option regarding speed. I like
DEoptim a lot, but I use it for more complicated problems when I can not find
simpler solution. Try adjusting parameters of it, it has 5 or 6 different
approaches to the problem. Adding jitter helps in some cases(might slow process
a bit, but not sure). I used it when I was optimising with respect to
non-linear functions of portfolio evolution as drawdown.
Kind regards,--
Dominykas Grigonis
On Thursday, 6 June 2013 at 07:55, Bastian Offermann wrote:
Hi all,
I am working on a large scale portfolio optimization problem with up to
500 assets. My objective function is simple
w*returns - 1/2 * 1/constant * w * Matrix * w
subject to sum(w) == 1 and w is a vector of weights with 0 <= w[i] <= 1
for all i = 1, ..., n.
I have tried quadprog, alabama and DEoptim. What are your experiences
with those and possibly other options?
Thanks in advance!
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