tulip.jl-6dd1b50a-3aae-11e9-10b5-ef983d2400fa
Last mirrored from https://github.com/ds4dm/Tulip.jl.git on 2019-11-19T07:08:25.264-05:00 by @UnofficialJuliaMirrorBot via Travis job 481.38 , triggered by Travis cron job on branch "master"
https://github.com/unofficialjuliamirror/tulip.jl-6dd1b50a-3aae-11e9-10b5-ef983d2400fa
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.3%) to scientific vocabulary
Repository
Last mirrored from https://github.com/ds4dm/Tulip.jl.git on 2019-11-19T07:08:25.264-05:00 by @UnofficialJuliaMirrorBot via Travis job 481.38 , triggered by Travis cron job on branch "master"
Basic Info
- Host: GitHub
- Owner: UnofficialJuliaMirror
- License: other
- Language: Julia
- Default Branch: master
- Size: 299 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Tulip
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Overview
Tulip is an open-source interior-point solver for linear optimization, written in pure Julia. It implements the homogeneous primal-dual interior-point algorithm with multiple centrality corrections, and therefore handles unbounded and infeasible problems. Tulip’s main feature is that its algorithmic framework is disentangled from linear algebra implementations. This allows to seamlessly integrate specialized routines for structured problems.
Installation
Just install like any Julia package
julia
] add Tulip
Usage
The recommended way of using Tulip is through JuMP and/or MathOptInterface (MOI).
The low-level interface is still under development and will change in the future. The user-exposed MOI interface is more stable.
Using with JuMP
Tulip follows the syntax convention PackageName.Optimizer:
```julia using JuMP import Tulip
model = Model(with_optimizer(Tulip.Optimizer)) ```
Using with MOI
The type Tulip.Optimizer is parametrized by the type of numerical data.
This allows to solve problem in higher numerical precision.
See the documentation for more details.
```julia import MathOptInterface MOI = MathOptInterface import Tulip
model = Tulip.Optimizer{Float64}() # Create a model in Float64 precision model = Tulip.Optimizer() # Defaults to the above call model = Tulip.Optimizer{BigFloat}() # Create a model in BigFloat precision ```
Citing Tulip.jl
If you use Tulip in your work, we kindly ask that you cite the following reference. The PDF is freely available here, and serves as a user manual for advanced users.
@TechReport{Tulip.jl,
title = {{Tulip}.jl: an open-source interior-point linear optimization
solver with abstract linear algebra},
url = {https://www.gerad.ca/fr/papers/G-2019-36},
Journal = {Les Cahiers du Gerad},
Author = {Anjos, Miguel F. and Lodi, Andrea and Tanneau, Mathieu},
year = {2019}
}
Owner
- Name: Unofficial Julia Mirror
- Login: UnofficialJuliaMirror
- Kind: organization
- Website: https://github.com/UnofficialJuliaMirror/MirrorUpdater.jl
- Repositories: 3
- Profile: https://github.com/UnofficialJuliaMirror
Mirror of all registered Julia packages. Updated weekly by @UnofficialJuliaMirrorBot. See also: @UnofficialJuliaMirrorSnapshots.
Citation (CITATION.bib)
@TechReport{Tulip.jl,
title = {{Tulip}.jl: an open-source interior-point linear optimization
solver with abstract linear algebra},
url = {https://www.gerad.ca/fr/papers/G-2019-36},
Journal = {Les Cahiers du Gerad},
Author = {Anjos, Miguel F. and Lodi, Andrea and Tanneau, Mathieu},
year = {2019}
}