An interface to using SDPA-GMP, SDPA-DD, and SDPA-QD in Julia
(http://sdpa.sourceforge.net). This package is registered in the
General registry; to install, type
] in the Julia command prompt, then enter
pkg> add SDPAFamily
SDPAFamily.Optimizer() to use this wrapper via
is an intermediate layer between low-level solvers (such as SDPA-GMP, SDPA-QD,
and SDPA-DD) and high level modelling languages, such as
Convex.jl 0.13+ supports MathOptInterface and can be used to solve problems with the solvers from this package.
JuMP currently only supports
Float64 numeric types, which means that problems
can only be specified to 64-bits of precision, and results can only be recovered
at that level of precision, when using JuMP. This is tracked in the issue
Here is a simple optimization problem formulated with Convex.jl:
using SDPAFamily, LinearAlgebra using Convex y = Semidefinite(3) p = maximize(eigmin(y), tr(y) <= 5; numeric_type = BigFloat) solve!(p, () -> SDPAFamily.Optimizer(presolve=true)) @show p.optval
See the documentation linked above for troubleshooting help and usage information.