psrenergy/dwaveneal.jl

🌊 D-Wave Neal Simulated Annealing Interface for JuMP

DWaveNeal.jl

⚠️ Warning This package was archived. Consider using DWave.jl instead.

D-Wave Neal Simulated Annealing Interface for JuMP

Installation

julia> import Pkg; Pkg.add("DWaveNeal")

julia> using DWaveNeal

Getting started

using JuMP
using DWaveNeal

model = Model(DWaveNeal.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.(model[:x]; result = i)
    yi = objective_value(model; result = i)

    println("[$i] f($(xi)) = $(yi)")
end

Note: The D-Wave Neal wrapper for Julia is not officially supported by D-Wave Systems. If you are a commercial customer interested in official support for Julia from DWave, let them know!

Note: If you are using DWaveNeal.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.

dwaveneal.jl's Issues

TagBot trigger issue

This issue is used to trigger TagBot; feel free to unsubscribe.

If you haven't already, you should update your TagBot.yml to include issue comment triggers.
Please see this post on Discourse for instructions and more details.

If you'd like for me to do this for you, comment TagBot fix on this issue.
I'll open a PR within a few hours, please be patient!