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Hi,
Currently, I am trying to solve a consensus-finding problem among a set of bi-level optimization problems (implemented via https://github.com/joaquimg/BilevelJuMP.jl). For this, the use of the DualDecomposition package would be particularly interesting as not many distributed algorithms can deal with the non-convex NLP subproblems.
However, currently, if the subproblems are formulated with BilevelJuMP the package raises an error:
ERROR: MethodError: Cannot `convert` an object of type BilevelModel to an object of type Model
Do you think the package could be seamlessly extended to such model instances?
Thanks in advance for the response!
The text was updated successfully, but these errors were encountered:
To use this package, the bilevel problem needs to be explicitly reformulated to a JuMP model. I think the BilevelJuMP package does not create a JuMP model. One idea is consulting with Joaquim for the BilevelJuMP package to return a JuMP model.
Hi,
Currently, I am trying to solve a consensus-finding problem among a set of bi-level optimization problems (implemented via https://github.com/joaquimg/BilevelJuMP.jl). For this, the use of the DualDecomposition package would be particularly interesting as not many distributed algorithms can deal with the non-convex NLP subproblems.
However, currently, if the subproblems are formulated with BilevelJuMP the package raises an error:
Do you think the package could be seamlessly extended to such model instances?
Thanks in advance for the response!
The text was updated successfully, but these errors were encountered: