Comments (2)
Hey @etatara. The set_model
function should still work, and the associated test seems to pass. As you said, you can always create an OptiNode
instead of a JuMP.Model
and use the same macros, but you shouldn't have to re-write your code since your original approach is supposed to be supported. This is definitely a bug. I'll take a look in the next couple days.
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Alright @etatara , this should be fixed by PR #40. Keep in mind, It only works if you use set_model
before you call optimize!
. It would be a bit harder to support incremental updates using set_model
, but you can still create the initial model this way and modify the optinodes afterwards.
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Related Issues (20)
- Adding nodes to a subgraph after the main graph's backend is initialized does not reset graph backend HOT 2
- Setting `Max` instead of `Min` in objective makes `objective_value` negative HOT 5
- append_to_backend accesses private methods from MOI.Utilities HOT 3
- Can Plasmo be used for nested decomposition (in principle, at least)? HOT 4
- Aggregated graph backend does not update variables correctly HOT 2
- Set model does not update object data in v0.6 HOT 1
- @variable and @constraint macros are very slow when defining over sets in v0.6 HOT 1
- Using a solver other than Ipopt HOT 2
- Adding variables or objective to overall `OptiGraph` object HOT 1
- Docs link in Readme still points to Zavalalab HOT 1
- Modeling with many optinodes does not scale HOT 1
- `aggregate` throws an error for some OptiGraphs when `max_depth` > 0 HOT 1
- Optigraph set_objective is too slow HOT 1
- Quadratic objectives with variables on separate nodes is not supported HOT 3
- Calling `optimize!` on an expanded subgraph resets the solution of a different subgraph HOT 2
- `dual(subgraph, link_ref)` does not work like `value(subgraph, var_ref)` HOT 1
- `unset_binary` function does not work after `optimize!` is called HOT 2
- Retrieving callback data for lazy constraints fails HOT 5
- Does Plasmo.jl decompose solving process? HOT 2
- `dual` does not work on linkconstraints set after `optimize!` is called HOT 4
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