diff --git a/src/server/BreCal/validators/validation_rule_functions.py b/src/server/BreCal/validators/validation_rule_functions.py
index d6b6fbc..ef44f08 100644
--- a/src/server/BreCal/validators/validation_rule_functions.py
+++ b/src/server/BreCal/validators/validation_rule_functions.py
@@ -134,8 +134,16 @@ class ValidationRuleBaseFunctions():
             participant_types = [ParticipantType.AGENCY.value, ParticipantType.MOORING.value, ParticipantType.PORT_ADMINISTRATION.value, ParticipantType.PILOT.value, ParticipantType.TUG.value]
         else:
             participant_types = [ParticipantType.AGENCY.value, ParticipantType.MOORING.value, ParticipantType.PILOT.value, ParticipantType.TUG.value]
+
+        agency_times = df_times.loc[df_times["participant_type"]==ParticipantType.AGENCY.value,:]
         df_times = df_times.loc[df_times["participant_type"].isin(participant_types),:]
 
+        
+        agency_time = [time_ for time_ in agency_times.loc[:,query].tolist() if isinstance(time_, pd.Timestamp)]
+        if not len(agency_time):
+            violation_state = False
+            return violation_state
+
         # exclude missing entries and consider only pd.Timestamp entries (which ignores pd.NaT/null entries)
         estimated_times = [time_ for time_ in df_times.loc[:,query].tolist() if isinstance(time_, pd.Timestamp)] # df_times = df_times.loc[~df_times[query].isnull(),:]
 
@@ -143,9 +151,18 @@ class ValidationRuleBaseFunctions():
         if len(estimated_times)==0:
             violation_state = False
             return violation_state
+        
+        # this (current) solution compares times to the reference (agency) time and checks if the difference is greater than 15 minutes
+        violation_state = ((np.max(estimated_times) - agency_time[0]) > pd.Timedelta("15min")) or ((agency_time[0] - np.min(estimated_times)) > pd.Timedelta("15min"))
 
-        difference = np.max(estimated_times) - np.min(estimated_times)
-        violation_state = difference > pd.Timedelta("15min")
+        # this solution to the rule compares all times to each other. When there is a total difference of more than 15 minutes, a violation occurs
+        # Consequently, it treats all times as equally important
+        # difference = np.max(estimated_times) - np.min(estimated_times)
+        # violation_state = difference > pd.Timedelta("15min")
+
+        # this solution clamps the times to 15 minute intervals and compares these values. When there is a single time difference, a violation occurs
+        # the drawback is that in some cases if there is a minimal difference say of 1 minute (:22 and :23 minutes after the hour) the violation is 
+        # triggered even though the times are very close to each other
 
         # apply rounding. For example, the agreement of different participants may be required to match minute-wise
         # '15min' rounds to 'every 15 minutes'. E.g., '2023-09-22 08:18:49' becomes '2023-09-22 08:15:00'
@@ -156,6 +173,8 @@ class ValidationRuleBaseFunctions():
         #    times_agency.eta_berth==times_mooring.eta_berth==times_portadministration.eta_berth==times_pilot.eta_berth==times_tug.eta_berth
         # n_unique_times = len(np.unique(estimated_times))
         # violation_state = n_unique_times!=1
+
+
         return violation_state
 
     def check_unique_shipcall_counts(self, query:str, times_agency:pd.DataFrame, rounding="min", maximum_threshold=3, all_times_agency=None)->bool: