[Coin-ipopt] how biggest problems can IPOP solve

[Xiaoming Yu]

Hi Dear All:

 

How biggest problems have been tested for IPOPT in terms of number of
design variables and inequality constraints? How efficient is the IPOPT
if the function evaluation and the first-order gradient computation (but
no second-order gradients) are very cheap ( in terms of CPU time on
faster  Intel machines). Our goal is to solve two  kinds of problems :

 


1) about 1-10 millions design variables but a few number of constraints


2) about 100-50K design variables and 500-100K constraints


 


Another question is if IPOPT use a "active constraints" concept. Active
constraints are the violated or near critical constraints. The gradients
are calculated for active constraints only. Thus, we can save times for
gradient computation (also less memory requirements). In engineering
problems, lots of constraints are inactive.


 

Thanks,

 

Xiaoming 

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