Add branch mostinfeas test

Author: Opt-Mucca

tests/test_branch_incomplete.py

@@ -0,0 +1,39 @@
+from pyscipopt import Branchrule, SCIP_RESULT
+from helpers.utils import random_mip_1
+
+import numpy as np
+
+
+class MostInfBranchRule(Branchrule):
+
+    def __init__(self, scip):
+        self.scip = scip
+
+    def branchexeclp(self, allowaddcons):
+
+        # Get the branching candidates. Only consider the number of priority candidates (they are sorted to be first)
+        # The implicit integer candidates in general shouldn't be branched on. Unless specified by the user
+        # npriocands and ncands are the same (npriocands are variables that have been designated as priorities)
+        branch_cands, branch_cand_sols, branch_cand_fracs, ncands, npriocands, nimplcands = self.scip.getLPBranchCands()
+
+        # Find the variable that is most fractional
+        best_cand_idx = 0
+        best_dist = np.inf
+        for i in range(npriocands):
+            if abs(branch_cand_fracs[i] - 0.5) <= best_dist:
+                best_dist = abs(branch_cand_fracs[i] - 0.5)
+                best_cand_idx = i
+
+        # Branch on the variable with the largest score
+        down_child, eq_child, up_child = self.model.branchVarVal(
+            branch_cands[best_cand_idx], branch_cand_sols[best_cand_idx])
+
+        return {"result": SCIP_RESULT.BRANCHED}
+
+
+def test_branch_mostinfeas():
+    scip = random_mip_1(node_lim=1000, small=True)
+    most_inf_branch_rule = MostInfBranchRule(scip)
+    scip.includeBranchrule(most_inf_branch_rule, "python-mostinf", "custom most infeasible branching rule",
+                           priority=10000000, maxdepth=-1, maxbounddist=1)
+    scip.optimize()