Merge branch 'master' into kaibel

.github/workflows/lint.yml

@@ -0,0 +1,18 @@
+name: Lint
+
+on: [push, pull_request]
+
+jobs:
+  lint:
+    name: lint/style-and-typos
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Black Formatting Check
+        uses: psf/black@stable
+        with:
+          options: "-S -C --check --diff"
+      - name: Spell Check
+        uses: crate-ci/typos@master
+        with:
+          config: ./.github/workflows/typos.toml

.github/workflows/typos.toml

@@ -0,0 +1,5 @@
+[default.extend-words]
+# Ignore HDA
+hda = "hda"
+HDA = "HDA"
+equil = "equil"

.gitignore

@@ -130,3 +130,5 @@ dmypy.json
 
 # Pycharm
 .idea/
+
+gdplib/*/benchmark_result/

CITATION.cff

@@ -0,0 +1,43 @@
+cff-version: 1.0.0
+message: "If you use this software, please cite it as below."
+authors:
+  - family-names: Bernal Neira
+    given-names: David E.
+    orcid: https://orcid.org/0000-0002-8308-5016
+  - family-names: Peng
+    given-names: Zedong
+    orcid: https://orcid.org/0000-0001-6001-1738
+  - family-names: Chen
+    given-names: Qi
+    orcid: https://orcid.org/0000-0002-2389-2238
+  - family-names: Liu
+    given-names: Yunshan
+  - family-names: Johnson
+    given-names: Emma
+    orcid: https://orcid.org/0000-0002-4285-5184
+title: "GDPLib: an open library of Generalized Disjunctive Programming (GDP) models"
+version: 1.0.0
+url: https://github.com/SECQUOIA/gdplib
+license-url: https://github.com/SECQUOIA/gdplib/blob/master/LICENSE
+preferred-citation:
+  type: incollection
+  booktitle: "Computer Aided Chemical Engineering"
+  volume: 49
+  start: 1285
+  end: 1290
+  title: "Advances in Generalized Disjunctive and Mixed-Integer Nonlinear Programming Algorithms and Software for Superstructure Optimization"
+  year:2022
+  publisher: "Elsevier"
+  authors: 
+  - family-names: "Bernal Neira"
+    given-names: "David E."
+  - family-names: "Liu"
+    given-names: "Yunshan"
+  - family-names: "Bynum"
+    given-names: "Michael L"
+  - family-names: "Laird"
+    given-names: "Carl D"
+  - family-names: "Siirola"
+    given-names: "John D"
+  - family-names: "Grossmann"
+    given-names: "Ignacio E"

benchmark.py

@@ -0,0 +1,109 @@
+import os
+import json
+import time
+import sys
+from datetime import datetime
+from importlib import import_module
+from pyomo.environ import *
+
+
+def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
+    """Benchmark the model using the given strategy and subsolver.
+
+    The result files include the solver output and the JSON representation of the results.
+
+    Parameters
+    ----------
+    model : PyomoModel
+        the model to be solved
+    strategy : string
+        the strategy used to solve the model
+    timelimit : int
+        the time limit for the solver
+    result_dir : string
+        the directory to store the benchmark results
+
+    Returns
+    -------
+    None
+    """
+    model = model.clone()
+    stdout = sys.stdout
+    if strategy in ["gdp.bigm", "gdp.hull"]:
+        transformation_start_time = time.time()
+        TransformationFactory(strategy).apply_to(model)
+        transformation_end_time = time.time()
+        with open(
+            result_dir + "/" + strategy + "_" + subsolver + ".log", "w"
+        ) as sys.stdout:
+            results = SolverFactory(subsolver).solve(
+                model, tee=True, timelimit=timelimit
+            )
+            results.solver.transformation_time = (
+                transformation_end_time - transformation_start_time
+            )
+            print(results)
+    elif strategy in [
+        "gdpopt.enumerate",
+        "gdpopt.loa",
+        "gdpopt.gloa",
+        "gdpopt.lbb",
+        "gdpopt.ric",
+    ]:
+        with open(
+            result_dir + "/" + strategy + "_" + subsolver + ".log", "w"
+        ) as sys.stdout:
+            results = SolverFactory(strategy).solve(
+                model,
+                tee=True,
+                nlp_solver=subsolver,
+                mip_solver=subsolver,
+                minlp_solver=subsolver,
+                local_minlp_solver=subsolver,
+                time_limit=timelimit,
+            )
+            print(results)
+
+    sys.stdout = stdout
+    with open(result_dir + "/" + strategy + "_" + subsolver + ".json", "w") as f:
+        json.dump(results.json_repn(), f)
+    return None
+
+
+if __name__ == "__main__":
+    instance_list = [
+        # "batch_processing",
+        # "biofuel",
+        # "disease_model",
+        # "gdp_col",
+        # "hda",
+        "jobshop",
+        # "kaibel",
+        # "logical",
+        # "med_term_purchasing",
+        # "methanol",
+        # "mod_hens",
+        # "modprodnet",
+        # "stranded_gas",
+        # "syngas",
+    ]
+    strategy_list = [
+        "gdp.bigm",
+        "gdp.hull",
+        "gdpopt.enumerate",
+        "gdpopt.loa",
+        "gdpopt.gloa",
+        "gdpopt.ric",
+    ]
+    current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+    timelimit = 600
+
+    for instance in instance_list:
+        print("Benchmarking instance: " + instance)
+        result_dir = "gdplib/" + instance + "/benchmark_result/"
+        os.makedirs(result_dir, exist_ok=True)
+
+        model = import_module("gdplib." + instance).build_model()
+
+        for strategy in strategy_list:
+            benchmark(model, strategy, timelimit, result_dir)

gdplib/__init__.py

@@ -2,9 +2,13 @@
 import gdplib.modprodnet
 import gdplib.biofuel
 import gdplib.logical  # Requires logical expression system
-import gdplib.pyomo_examples
 import gdplib.stranded_gas  # Requires logical expression system
 import gdplib.gdp_col
 import gdplib.hda
 import gdplib.kaibel
 import gdplib.methanol
+import gdplib.batch_processing
+import gdplib.jobshop
+import gdplib.disease_model
+import gdplib.med_term_purchasing
+import gdplib.syngas

gdplib/batch_processing/__init__.py

@@ -0,0 +1,3 @@
+from .batch_processing import build_model
+
+__all__ = ['build_model']