Switched from CBC to HiGHS

Author: Simon-Rey

pabutools/analysis/fairshare.py

@@ -1,4 +1,4 @@
-from pulp import LpProblem, LpMaximize, LpBinary, LpVariable, lpSum, PULP_CBC_CMD, value
+from pulp import LpProblem, LpMaximize, LpBinary, LpVariable, lpSum, value, HiGHS
 
 from pabutools.election import Instance, AbstractApprovalProfile
 from pabutools.fractions import frac
@@ -76,7 +76,7 @@ def min_distance_to_fair_share(instance: Instance, profile: AbstractApprovalProf
         mip_model += share_abs_vars[i] >= share_vars[i] - float(ballot_fairshare)
         mip_model += share_abs_vars[i] >= float(ballot_fairshare) - share_vars[i]
 
-    mip_model.solve(PULP_CBC_CMD(msg=False))
+    mip_model.solve(HiGHS(msg=False))
 
     return value(mip_model.objective)
 

pabutools/analysis/priceability.py

@@ -417,7 +417,7 @@ def priceable(
     else:
         model += 0  # No-op objective if none is specified
 
-    solver = pulp.PULP_CBC_CMD(msg=verbose, timeLimit=max_seconds)
+    solver = pulp.HiGHS(msg=verbose, timeLimit=max_seconds)
     status = model.solve(solver)
 
     if status not in [pulp.LpStatusOptimal]:

pabutools/election/instance.py

@@ -8,7 +8,7 @@
 
 from collections.abc import Collection, Generator
 
-from pulp import LpProblem, LpMaximize, LpVariable, LpBinary, lpSum, PULP_CBC_CMD, LpStatusOptimal, value
+from pulp import LpProblem, LpMaximize, LpVariable, LpBinary, lpSum, LpStatusOptimal, value, HiGHS
 
 from pabutools.utils import Numeric
 
@@ -185,7 +185,7 @@ def max_budget_allocation_cost(
     mip_model += lpSum(p_vars[p] * p.cost for p in projects) <= budget_limit
 
     # Solve the model
-    mip_model.solve(PULP_CBC_CMD(msg=False))
+    mip_model.solve(HiGHS(msg=False))
 
     if mip_model.status == LpStatusOptimal:
         max_cost = value(mip_model.objective)

pabutools/election/satisfaction/additivesatisfaction.py

@@ -6,7 +6,7 @@
 
 from collections.abc import Callable, Collection
 
-from pulp import LpProblem, LpMaximize, LpBinary, LpVariable, lpSum, PULP_CBC_CMD, value
+from pulp import LpProblem, LpMaximize, LpBinary, LpVariable, lpSum, value, HiGHS
 
 from pabutools.utils import Numeric
 
@@ -794,7 +794,7 @@ def preprocessing(
             # Budget constraint
             mip_model += lpSum(p_vars[p] * p.cost for p in instance) <= instance.budget_limit
 
-            mip_model.solve(PULP_CBC_CMD(msg=False))
+            mip_model.solve(HiGHS(msg=False))
 
             res = value(mip_model.objective)
 

pabutools/rules/maximin_support.py

@@ -8,7 +8,7 @@
 
 from collections.abc import Collection
 
-from pulp import LpProblem, LpMinimize, LpVariable, lpSum, LpStatusOptimal, value, PULP_CBC_CMD
+from pulp import LpProblem, LpMinimize, LpVariable, lpSum, LpStatusOptimal, value, HiGHS
 
 from pabutools.election import (
     Instance,
@@ -152,7 +152,7 @@ def _compute_optimal_load(projects, profile):
 
     prob += z  # Objective: minimize max load
 
-    status = prob.solve(PULP_CBC_CMD(msg=False))
+    status = prob.solve(HiGHS(msg=False))
 
     # This can mean a project that no one approves of for instance
     if status != LpStatusOptimal:

pabutools/rules/maxwelfare.py

@@ -9,7 +9,7 @@
 
 import math
 
-from pulp import LpProblem, LpMaximize, LpVariable, LpBinary, lpSum, PULP_CBC_CMD, value, LpStatusOptimal
+from pulp import LpProblem, LpMaximize, LpVariable, LpBinary, lpSum, value, LpStatusOptimal, HiGHS
 
 from pabutools.election import (
     Instance,
@@ -83,7 +83,7 @@ def max_additive_utilitarian_welfare_ilp_scheme(
     available_budget = instance.budget_limit - total_cost(initial_budget_allocation)
     mip_model += lpSum(p_vars[p] * p.cost for p in p_vars) <= available_budget
 
-    mip_model.solve(PULP_CBC_CMD(msg=False))
+    mip_model.solve(HiGHS(msg=False))
     opt_value = value(mip_model.objective)
 
     # First allocation
@@ -113,7 +113,7 @@ def max_additive_utilitarian_welfare_ilp_scheme(
                         lpSum(p_vars[p] for p in p_vars if p not in previous_partial_alloc)
                 ) <= len(previous_partial_alloc) - 1
 
-        mip_model.solve(PULP_CBC_CMD(msg=False))
+        mip_model.solve(HiGHS(msg=False))
 
         if mip_model.status != LpStatusOptimal:
             break

pyproject.toml

@@ -31,7 +31,7 @@ dependencies = [
     "preflibtools>=2.0.33",
     "natsort",
     "pulp",
-    "gurobipy"
+    "highspy"
 ]
 
 [project.optional-dependencies]