PySA Simulated Annealing Interface for JuMP
julia> import Pkg; Pkg.add("PySA")
julia> using PySA
using JuMP
using PySA
model = Model(PySA.Optimizer)
n = 3
Q = [ -1 2 2
2 -1 2
2 2 -1 ]
@variable(model, x[1:n], Bin)
@objective(model, Min, x' * Q * x)
optimize!(model)
for i = 1:result_count(model)
xi = value.(x; result = i)
yi = objective_value(model; result = i)
println("[$i] f($(xi)) = $(yi)")
end
Note: The PySA wrapper for Julia is not officially supported by the National Aeronautics and Space Administration. If you are interested in official support for Julia from NASA, let them know!
Note: If you are using PySA.jl
in your project, we recommend you to include the .CondaPkg
entry in your .gitignore
file. The PythonCall
module will place a lot of files in this folder when building its Python environment.