Revisit fixed variables treatment #360
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* Change the behavior of MakeParameter, depending on the callback:
- `SparseCallback`: remove the fixed variables and reduce problem's dimension in MadNLP
- `DenseCallback`: keep the fixed variables frozen (as done previously)
* Add a new `fixed_handler` if the problem has no fixed variable: `NoFixedVariable`.
* Ensure we always interact to the nonlinear program `nlp` through the
callback wrapper `cb` to avoid side effect.
* Remove the function `get_index_constraint` and stores indexes directly
in the callback wrapper `cb`.
* Fix the computation of the bound's multipliers for fixed variables.
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Results on CUTEst are out (comparing this PR with MadNLP 0.8.4). It looks like we just improve very slightly the total number of iterations. In terms of computation time, we are slower. Also we are less robust now than before. Currently investigating what's going on. |
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Benchmark is improved if we use the fix in #361 in this PR: |
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SparseCallback: remove the fixed variables and reduce problem's dimension in MadNLPDenseCallback: keep the fixed variables frozen (as done previously). On the contrary toSparseCallback, we don't remove the fixed variables as this would require duplicating the Hessian and the Jacobian matrices to evaluate the model, which could be expensive if we are memory bounded.fixed_handlerif the problem has no fixed variable:NoFixedVariable.nlpthrough the callback wrappercbto avoid side effect.get_index_constraintand stores indexes directly in the callback wrappercb.Solve #70, #229
Warning: this PR adds a small breaking change in
create_kkt_system(we removeind_consfrom the arguments) but I think it's worth the change, as the previous situation was error prone. Now, we make sure we store all the problem's information inside the callback wrappercb.Preliminary results on
space_shuttle_reentryshows that the current PR improves slightly the convergence (less iterations, less feasibility restoration), see the logs in attachment:Benchmark on CUTEst is under way.