LinQuadOptInterface.jl
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JuliaOpt
Intermediate wrapper of MOI for some linear quadratic solvers
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```julia import Gurobi import MathOptInterface MOI = MathOptInterface m = Gurobi.Optimizer() x = MOI.add_variable(m) # Create two linear constraints, wrapped in a single VectorAffineFunction constraint n = 2 c1 =...
From https://github.com/tkoolen/Parametron.jl/issues/104, https://github.com/JuliaOpt/LinQuadOptInterface.jl/blob/7f4d09bf834f1ba3e2938397dbfae5c7108fe281/src/constraints/scalaraffine.jl#L264 means that if `previous.constant` is `NaN` or `Inf`, the value that is passed to `change_rhs_coefficient!` is incorrect. See also https://github.com/oxfordcontrol/OSQP.jl/issues/54. CC: @rdeits.
Currently we have a dict mapping variables to indices. We only actualy need that onde a variable is deleted, before deletion the variable reference already have the correct index. By...
Add data optimizers, useful for educational purposes. Students can implement their own simplex method, interior point, b&b and so on.
Instead of passing off to the solver https://github.com/JuliaOpt/LinQuadOptInterface.jl/blob/812d334cc26394f4409c782ebdf6b4cd16e9debe/src/solve.jl#L244-L246 we should implement this ourselves to avoid issues such as https://github.com/JuliaOpt/MathOptInterface.jl/issues/590.
Related to: https://github.com/JuliaOpt/JuMP.jl/issues/1905 We can exploit the fact that LQOI creates variable with increasing internal indices. We would use something similar to JuMP’s 0.18 implementarion for canonicalizing affine expressions.
An efficient implementation of `MOI.copy_to` is needed when JuMP is used in `AUTOMATIC` mode. See https://github.com/JuliaOpt/Gurobi.jl/pull/188#issuecomment-459385303.
Currently, LQOI essentially keeps the constant part of the objective for itself, storing it in a field of the optimizer rather than actually passing it to the solver. However, there...
Currently we only get the farkas dual for constraints: https://github.com/JuliaOpt/LinQuadOptInterface.jl/blob/d6957f357227e692c0e15bd6c64e9d0a37b7b1f1/src/solve.jl#L58 However, `linear12` needs it for variable bounds.