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Description
Currently, the parser (a series of code scripts) only grabs the first problem from the sddp.jl graph.
How I currently bring problems from sddp.jl:
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I first save the file related to the first problem:
DecisionRules.jl/examples/HydroPowerModels/run_sddp.jl
Lines 40 to 44 in 5f413f5
# ## Save subproblem # results = HydroPowerModels.simulate(m, 2); # model = m.forward_graph[1].subproblem # delete(model, all_variables(model)[findfirst(x -> x == "", name.(all_variables(model)))]) # JuMP.write_to_file(model, joinpath(case_dir, string(formulation)) * ".mof.json") -
Then, by knowing the name of the variables that my sddp.jl builder creates and how sddp.jl names incoming and outgoing stages, I transform the variables that represent parameters to the choice of parameter representation:
- Context sddp.jl: parameters there are just fixed variables (jump name for variable in equality constraint) - so I need to find the variable and the constraint (to delete it if needed or save the reference).
- DecisionRules.jl will soon only allow for parameters to be just MOI.Parameter.
- code: https://github.com/LearningToOptimize/DecisionRules.jl/blob/main/examples/HydroPowerModels/load_hydropowermodels.jl
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