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Add README for JuMP
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![Logo](https://raw.githubusercontent.com/hdavid16/DisjunctiveProgramming.jl/master/logo.png) | ||
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[`DisjunctiveProgramming.jl`](https://github.com/hdavid16/DisjunctiveProgramming.jl) is a | ||
`JuMP` extension for expressing and solving Generalized Disjunctive Programs. | ||
[Generalized Disjunctive Programming](chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/http://egon.cheme.cmu.edu/Papers/IMAGrossmannRuiz.pdf) | ||
(GDP) is a modeling paradigm for easily modeling logical conditions which can be reformulated | ||
into a variety of mixed-integer programs. | ||
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| **Current Version** | **Documentation** | **Build Status** | **Citation** | | ||
|:---------------------------------------:|:-------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|:--------------------------------------:| | ||
| [![](https://docs.juliahub.com/DisjunctiveProgramming/version.svg)](https://juliahub.com/ui/Packages/General/DisjunctiveProgramming) | [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://hdavid16.github.io/DisjunctiveProgramming.jl/stable/) | [![Build Status](https://github.com/infiniteopt/InfiniteOpt.jl/workflows/CI/badge.svg?branch=master)](https://github.com/hdavid16/DisjunctiveProgramming.jl/actions?query=workflow%3ACI) [![codecov.io](https://codecov.io/gh/hdavid16/DisjunctiveProgramming.jl/graph/badge.svg?token=3FRPGMWF0J)](https://codecov.io/gh/hdavid16/DisjunctiveProgramming.jl) | [![arXiv](https://img.shields.io/badge/arXiv-2304.10492-b31b1b.svg)](https://arxiv.org/abs/2304.10492) | | ||
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`DisjunctiveProgramming` builds upon `JuMP` to add support GDP modeling objects which include: | ||
- Logical variables (``Y \in \{\text{False}, \text{True}\}``) | ||
- Disjunctions | ||
- Logical constraints (also known as propositions) | ||
- Cardinality constraints | ||
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It also supports automatic conversion of the GDP model into a regular mixed-integer `JuMP` model | ||
via a variety of reformulations which include: | ||
- Big-M | ||
- Hull | ||
- Indicator constraints | ||
Moreover, `DisjunctiveProgramming` provides an extension API to easily add new reformulation methods. | ||
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## License | ||
`InfiniteOpt` is licensed under the [MIT "Expat" license](https://github.com/hdavid16/DisjunctiveProgramming.jl/blob/master/LICENSE). | ||
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## Installation | ||
`DisjunctiveProgramming.jl` is a registered [Julia](https://julialang.org/) package and | ||
can be installed by entering the following in the REPL. | ||
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```julia | ||
julia> import Pkg; Pkg.add("DisjunctiveProgramming") | ||
``` | ||
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## Documentation | ||
Please visit our [documentation pages](https://hdavid16.github.io/DisjunctiveProgramming.jl/stable/) | ||
to learn more. | ||
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## Citing | ||
[![arXiv](https://img.shields.io/badge/arXiv-2304.10492-b31b1b.svg)](https://arxiv.org/abs/2304.10492) | ||
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If you use DisjunctiveProgramming.jl in your research, we would greatly appreciate your | ||
citing it. | ||
```latex | ||
@article{perez2023disjunctiveprogramming, | ||
title={DisjunctiveProgramming. jl: Generalized Disjunctive Programming Models and Algorithms for JuMP}, | ||
author={Perez, Hector D and Joshi, Shivank and Grossmann, Ignacio E}, | ||
journal={arXiv preprint arXiv:2304.10492}, | ||
year={2023} | ||
} | ||
``` |