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wouterbles merged 1 commit into from
Apr 27, 2026
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docs: add conda instructions #32

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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -4,6 +4,7 @@

- Removed pre-v2 dead code (model.py, pyaugmecon.py, process_handler.py, queue_handler.py, solver_adapter.py, solver_process.py) superseded by the solver/ subpackage.


## 2.0.0 - 2026-04-26

### Breaking changes
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18 changes: 17 additions & 1 deletion README.md
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Expand Up @@ -37,14 +37,17 @@ PyAUGMECON solves multi-objective optimization problems defined in [Pyomo](https

## Installation

PyAUGMECON does not bundle a solver. Pick one when installing:
PyAUGMECON is published on [PyPI](https://pypi.org/project/pyaugmecon) and [conda-forge](https://anaconda.org/conda-forge/pyaugmecon). The base package ships without a solver, so pick a solver extra when installing:

```bash
# Recommended: uv (https://docs.astral.sh/uv/)
uv add "pyaugmecon[highs]"

# Or with pip
pip install "pyaugmecon[highs]"

# Or with conda / mamba
conda install -c conda-forge pyaugmecon
```

Available solver extras:
Expand All @@ -65,6 +68,19 @@ Solvers not bundled as extras but supported when their binary is on `PATH`:

Once installed, pass `solver_name="scip"` or `solver_name="cplex"`. You can also install CBC manually instead of `pyaugmecon[cbc]`; `cbcbox` is typically faster than a system-installed CBC binary (e.g. 85 s vs 471 s on `3kp40`), as it ships AVX2-optimized builds with bundled OpenBLAS.

> **conda solver names:** PyPI `[solver]` extras don't apply to conda. Install solvers as separate packages:
>
> | Solver | conda package |
> | --- | --- |
> | HiGHS | `conda install -c conda-forge highspy` |
> | Gurobi | `conda install -c gurobi gurobi` |
> | XPRESS | `conda install -c fico-xpress xpress` |
> | CPLEX | `conda install -c ibmdecisionoptimization cplex` |
> | CBC | `conda install -c conda-forge coincbc` |
> | SCIP | `conda install -c conda-forge scip` |
>
> Gurobi, XPRESS, and CPLEX are distributed via vendor-specific channels (not conda-forge) and require a license to use.

## Quick start

Define a Pyomo model with objectives in an `ObjectiveList` named `obj_list`, then pass it to PyAUGMECON. Defaults are sensible, so a minimal run takes no config:
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