more balanced scores

backend/src/utils/optimizer.py

@@ -203,7 +203,7 @@ class Optimizer:
         return c, A_ub, [max_steps]
 
 
-    def respect_number(self, L: int):
+    def respect_number(self, L, max_landmarks: int):
         """
         Generate constraints to ensure each landmark is visited only once and cap the total number of visited landmarks.
 
@@ -224,7 +224,7 @@ class Optimizer:
             b.append(1)
 
         A = np.vstack((A, ones*L))
-        b.append(self.max_landmarks+1)
+        b.append(max_landmarks+1)
 
         return A, b
 
@@ -433,6 +433,7 @@ class Optimizer:
             self,
             max_time: int,
             landmarks: list[Landmark],
+            max_landmarks: int = None
         ) -> list[Landmark]:
         """
         Main optimization pipeline to solve the landmark visiting problem.
@@ -443,15 +444,18 @@ class Optimizer:
         Args:
             max_time (int): Maximum time allowed for the tour in minutes.
             landmarks (list[Landmark]): List of landmarks to visit.
+            max_landmarks (int): Maximum number of landmarks visited
         Returns:
             list[Landmark]: The optimized tour of landmarks with updated travel times, or None if no valid solution is found.
         """
+        if max_landmarks is None :
+            max_landmarks = self.max_landmarks
 
         L = len(landmarks)
 
         # SET CONSTRAINTS FOR INEQUALITY
         c, A_ub, b_ub = self.init_ub_dist(landmarks, max_time)          # Add the distances from each landmark to the other
-        A, b = self.respect_number(L)                     # Respect max number of visits (no more possible stops than landmarks). 
+        A, b = self.respect_number(L, max_landmarks)                                   # Respect max number of visits (no more possible stops than landmarks). 
         A_ub = np.vstack((A_ub, A), dtype=np.int16)
         b_ub += b
         A, b = self.break_sym(L)                                         # break the 'zig-zag' symmetry