Comments (3)
I've given up on compression of terms for quads, I would want to do it in a way that doesn't take n^2 memory, so need a different approach from the IndexedVector way (which was nice for making the affToStr issues)
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Goes gurobi accept duplicate quadratic terms? Compressing aff was important because solvers didn't like duplicate linear indices, but if gurobi doesn't care then it's not really an issue for now.
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http://www.gurobi.com/documentation/5.5/reference-manual/node16
"The Gurobi interface is built around quadratic terms, rather than a Q matrix. If your quadratic objective contains a term 2 x y, you can enter it as a single term, 2 x y, or as a pair of terms, x y and y x."
Seems promising
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Related Issues (20)
- NumFOCUS: GSoC 2024 Update HOT 1
- Error vcat(::NonlinearExpr, ::VariableRef, ::Float64) HOT 5
- Increase performance of SOC constraints HOT 4
- Iterating SparseAxisArray does not preserve order HOT 4
- How to improve the speed to build a complex model? HOT 2
- Coefficients of complex variables created with a GenericModel are always Float64
- LinearAlgebra.hermitian is incorrect
- *(::Real, ::Hermitian) is not hermitian HOT 5
- Cannot `convert` an object of type Float64 to an object of type JuMP.NonlinearExpr HOT 3
- Documentation Request: List whether a solver supports Indicator Constraints HOT 4
- Bullet point alignment in bibliography HOT 9
- Multiplication of matrix expression and variables leads to stack overflow and matmul error HOT 4
- Multiple Ranges for variables HOT 3
- Y' when Y is of type ::Matrix{NonlinearExpr} HOT 1
- Poor performance in complementarity models HOT 23
- Add a method for Complex(a,b) HOT 8
- MethodError with empty summations HOT 1
- Nonlinear subexpressions
- Should error when trying to mix `NonlinearExpression` and `GenericNonlinearExpr` HOT 1
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