backend/src/main.py

@@ -70,6 +70,7 @@ def new_trip(preferences: Preferences,
                               osm_type='start',
                               osm_id=0,
                               attractiveness=0,
+                              duration=0,
                               must_do=True,
                               n_tags = 0)
 
@@ -79,6 +80,7 @@ def new_trip(preferences: Preferences,
                             osm_type='end',
                             osm_id=0,
                             attractiveness=0,
+                            duration=0,
                             must_do=True,
                             n_tags=0)
 

backend/src/optimization/optimizer.py

@@ -87,7 +87,7 @@ class Optimizer:
 
         # inequality matrix and vector
         A_ub = np.zeros(L*L, dtype=np.int16)
-        b_ub = round(max_time*self.overshoot)
+        b_ub = round(max_time*(1.1+max_time*self.overshoot))
 
         for i, spot1 in enumerate(landmarks) :
             c[i] = spot1.attractiveness
@@ -489,6 +489,17 @@ class Optimizer:
         return L
 
 
+    def warm_start(self, x: list[pl.LpVariable], L: int) :
+
+        for i in range(L*L) :
+            x[i].setInitialValue(0)
+            
+        x[1].setInitialValue(1)
+        x[2*L-1].setInitialValue(1)
+
+        return x
+
+
     def pre_processing(self, L: int, landmarks: list[Landmark], max_time: int, max_landmarks: int | None) :
         """
         Preprocesses the optimization problem by setting up constraints and variables for the tour optimization.
@@ -539,6 +550,7 @@ class Optimizer:
         self.respect_order(prob, x, L)                   # Respect order of visit (only works when max_time is limiting factor)
         self.respect_user_must(prob, x, L, landmarks)    # Force to do/avoid landmarks set by user.
 
+        # return prob, self.warm_start(x, L)
         return prob, x
 
 
@@ -561,7 +573,7 @@ class Optimizer:
         prob, x = self.pre_processing(L, landmarks, max_time, max_landmarks)
 
         # Solve the problem and extract results.
-        prob.solve(pl.PULP_CBC_CMD(msg=False, gapRel=0.1))
+        prob.solve(pl.PULP_CBC_CMD(msg=False, gapRel=0.1, timeLimit=10, warmStart=False))
         status = pl.LpStatus[prob.status]
         solution = [pl.value(var) for var in x]  # The values of the decision variables (will be 0 or 1)
 

backend/src/parameters/landmark_parameters.yaml

@@ -1,12 +1,12 @@
 city_bbox_side: 7500 #m
 radius_close_to: 50
-church_coeff: 0.65
+church_coeff: 0.55
-nature_coeff: 1.35
+nature_coeff: 1.4
 overall_coeff: 10
 tag_exponent: 1.15
 image_bonus: 1.1
 viewpoint_bonus: 5
-wikipedia_bonus: 1.1
+wikipedia_bonus: 1.25
 name_bonus: 3
 N_important: 40
 pay_bonus: -1

backend/src/parameters/optimizer_parameters.yaml

@@ -3,4 +3,4 @@ detour_corridor_width: 300
 average_walking_speed: 4.8
 max_landmarks: 10
 max_landmarks_refiner: 20
-overshoot: 1.1
+overshoot: 0.0016

backend/src/structs/landmark.py

@@ -51,7 +51,7 @@ class Landmark(BaseModel) :
     website_url : Optional[str] = None
     wiki_url : Optional[str] = None
     description : Optional[str] = None                          # TODO future
-    duration : Optional[int] = 0
+    duration : Optional[int] = 5
     name_en : Optional[str] = None
 
     # Unique ID of a given landmark

backend/src/tests/test_main.py

@@ -50,7 +50,6 @@ def test_turckheim(client, request):    # pylint: disable=redefined-outer-name
     # checks :
     assert response.status_code == 200  # check for successful planning
     assert isinstance(landmarks, list)  # check that the return type is a list
-    assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2, f"Trip duration not within 20\% of desired length"
     assert len(landmarks) > 2           # check that there is something to visit
     assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
     assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"

backend/src/utils/landmarks_manager.py

@@ -294,8 +294,6 @@ class LandmarkManager:
                     elif value == 'cathedral' :
                         landmark.is_place_of_worship = False
                         landmark.duration = 10
-                    else :
-                        landmark.duration = 5
 
                 else:
                     self.set_landmark_score(landmark, landmarktype, preference_level)