diff --git a/domain/modelling/optimisation/optimiser.py b/domain/modelling/optimisation/optimiser.py
index a40db733c..afb3fc4e8 100644
--- a/domain/modelling/optimisation/optimiser.py
+++ b/domain/modelling/optimisation/optimiser.py
@@ -454,7 +454,7 @@ def _repair_to_target(
     baseline_epc: EpcPropertyData,
     budget: Optional[float],
     target_sap: float,
-    objective: Callable[[Score], float] = sap_rating,
+    objective: Callable[[Score], float],
 ) -> OptimisedPackage:
     """Inject dependencies onto the warm-start, re-score for the truth, then
     greedy-add the untreated-group Option with the best marginal objective-per-£
@@ -522,15 +522,16 @@ def _best_repair_candidate(
     baseline_epc: EpcPropertyData,
     current: Score,
     budget: Optional[float],
-    objective: Callable[[Score], float] = sap_rating,
+    objective: Callable[[Score], float],
 ) -> Optional[ScoredOption]:
-    """The untreated-group Option giving the best **marginal** SAP-per-£ when
-    added to the current package — re-scored (not the role-1 signal) with any
-    ventilation dependency it newly triggers folded in, so both its SAP and its
-    incremental cost are truthful. Affordable when the resulting whole-package
+    """The untreated-group Option giving the best **marginal** objective-per-£
+    when added to the current package — re-scored (not the role-1 signal) with
+    any ventilation dependency it newly triggers folded in, so both its gain and
+    its incremental cost are truthful. Affordable when the resulting whole-package
     cost is within ``budget`` and strictly improving. None if there is none."""
     used: set[int] = _used_group_indices(groups, chosen)
     base_cost: float = _package_cost(_inject(chosen, dependencies))
+    current_value: float = objective(current)
     best: Optional[ScoredOption] = None
     best_ratio: float = 0.0
     for index, group in enumerate(groups):
@@ -544,7 +545,7 @@ def _best_repair_candidate(
             if budget is not None and package_cost > budget:
                 continue
             trial: Score = _score(scorer, baseline_epc, trial_selected)
-            marginal: float = objective(trial) - objective(current)
+            marginal: float = objective(trial) - current_value
             if marginal <= 0.0:
                 continue
             incremental: float = package_cost - base_cost