[Ipopt] Is IPOPT ok for small quadratic problem ?

[Stefan Vigerske]

Hi,

IPOPT targets large-scale general nonlinear programs.
A good specialized QP solver can give you much better performance than 
Ipopt, as, indeed, it has less overhead, and, second, it can do some 
algorithmic tricks that are not possible for general NLPs.

If you still want to use Ipopt for QPs, you should enable the options 
jac_c_constant, jac_d_constant, and hessian_constant, so you can at 
least avoid recomputing Jacobian and Hessian in each point.

Stefan

On 01/16/2014 05:15 PM, Antonello Lobianco wrote:
> Hello,
> I develop in C++ a scientific model where I already use IPOPT (together
> with ADOL-C and ColPack) to solve a large nonlinear problem.
>
> Now I need, in an other part of the model, to solve many (~10,000 per
> simulation year) small quadratic problems of this form:
>
> min
>    sum_i sum_j  a_{i,j} x_i x_j
> s.t.
>    sum_i x_i = 1
>    x_i >= 0
>    sum_i x_i b_i = c
>
> with i=j ~ 10 and a_{i,j} >=0 for i = j
>
>
> Do you suggest me to use IPOPT also for these problems or would it be
> better to use a solver that is specialized in small quadratic programming
> (little initialisation costs) ?
>
> Thanks,
>    Antonello
>
>
>
>
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