https://github.com/juliaqubo/pysa.jl

JuMP wrapper for NASA PySA (ft QUBODrivers.jl)
https://github.com/juliaqubo/pysa.jl

julia jump metaheuristics optimization parallel-tempering

Last synced: about 24 hours ago
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JuMP wrapper for NASA PySA (ft QUBODrivers.jl)

• Host: GitHub
• URL: https://github.com/juliaqubo/pysa.jl
• Owner: JuliaQUBO
• License: mit
• Created: 2023-03-31T14:05:32.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-08-19T23:11:38.000Z (3 months ago)
• Last Synced: 2024-08-20T03:28:18.307Z (3 months ago)
• Topics: julia, jump, metaheuristics, optimization, parallel-tempering
• Language: Julia
• Homepage: https://psrenergy.github.io/QUBODrivers.jl/
• Size: 26.4 KB
• Stars: 2
• Watchers: 5
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PySA.jl

[![DOI](https://zenodo.org/badge/621844685.svg)](https://zenodo.org/badge/latestdoi/621844685)

[![QUBODRIVERS](https://img.shields.io/badge/Powered%20by-QUBODrivers.jl-%20%234063d8)](https://github.com/psrenergy/QUBODrivers.jl)

[PySA](https://github.com/nasa/pysa) Simulated Annealing Interface for JuMP

## Installation

```julia

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

julia> using PySA

```

## Getting started

```julia

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`](https://github.com/cjdoris/PythonCall.jl) module will place a lot of files in this folder when building its Python environment._