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Hello IPOPT community,<br>
<br>
I am trying to pose an NLP where the number of equality constraints
is greater than the number of decision variables (i.e., an
over-determined system) and the solver immediately exits with a <font
face="Courier New, Courier, monospace">Not_Enough_degrees_Of_Freedom</font>
error. Basically there are some equality constraints that fix some
of the variables.<br>
<br>
Clearly my problem is formulation related and I could reformulate
the equality constraints to two inequality constraints using a small
tolerance, but I rather not if possible.<br>
<br>
Note, I'm using the matlab interface to ipopt and directly
specifying all constraints/sparsity pattern, but I'm using the
limited-memory Hessian approximation.<br>
<br>
My first question: does the matlab interface expose all possible
ipopt solver options to the user ? (I assume so, since I didn't
receive any errors)<br>
<br>
Second, I tried to change the <font face="Courier New, Courier,
monospace">fixed_variable_treatment to relax_bounds</font> but it
didn't seem to help. I thought this would at least prevent the <font
face="Courier New, Courier, monospace">Not_Enough_degrees_Of_Freedom</font>
error flag from occurring.<br>
<br>
Note, I've tried this problematic formulation using knitro and the
solver proceeds with only a warning stating that there are more
equality constraints than variables. Also, snopt handles the problem
with no issues.<br>
<br>
Does anyone have any ideas to get around this problem.<br>
<br>
Thanks,<br>
Ian.<br>
<br>
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