Add infeasibility solving feature for dense and sparse backends #241
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jcarpent
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jcarpent
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jcarpent
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Co-authored-by: Justin Carpentier <justin.carpentier@inria.fr>
Co-authored-by: Justin Carpentier <justin.carpentier@inria.fr>
Co-authored-by: Justin Carpentier <justin.carpentier@inria.fr>
jcarpent
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Add a feature for solving closest feasible problem (in L_2 sense) if the original problem is detected as being primal infeasible.
The feature is available for dense and sparse backends with a boolean option in the Settings subclass.
The optimal shifts (making the original problem primal feasible) are available as new results variables in the Results subclass.
The whole feature is documented and unit tested in C++ and python.