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Merge branch 'main' into devcontainers
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Cargo.toml

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@@ -15,7 +15,8 @@ categories = ["mathematics", "algorithms", "science", "api-bindings", "data-stru
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default = ["coin_cbc", "singlethread-cbc"]
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singlethread-cbc = ["coin_cbc?/singlethread-cbc"]
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scip = ["russcip"]
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all_default_solvers = ["coin_cbc", "microlp", "lpsolve", "highs", "russcip", "lp-solvers", "clarabel"] # cplex-rs is not included because it is incompatible with lpsolve
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scip_bundled = ["russcip/bundled"]
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all_default_solvers = ["coin_cbc", "microlp", "lpsolve", "highs", "russcip/bundled", "lp-solvers", "clarabel"] # cplex-rs is not included because it is incompatible with lpsolve
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clarabel-wasm = ["clarabel/wasm"]
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minilp = ["microlp"] # minilp is not maintained anymore, we use the microlp fork instead
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README.md

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SCIP is currently one of the fastest open-source solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price. It allows for total control of the solution process and the access of detailed information down to the guts of the solver.
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`good_lp` uses SCIP through the its rust interface [russcip](https://github.com/mmghannam/russcip). To use this feature you will need to install SCIP. The easiest way to do it is to install a precompiled package from [here](https://scipopt.org/index.php#download) or through conda by running
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`good_lp` uses SCIP through its rust interface [russcip](https://github.com/mmghannam/russcip) which can ship a precompiled binary. The easiest way to use SCIP with `good_lp` is therefore to enable the `scip_bundled` feature.
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You can also use a custom installation of SCIP by enabling the `scip` feature instead. A good way of installing SCIP is by downloading a precompiled package from [here](https://scipopt.org/index.php#download) or through conda by running
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```
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conda install --channel conda-forge scip
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```

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