diff --git a/examples/hotelling_law/hotelling_law/agents.py b/examples/hotelling_law/hotelling_law/agents.py
index d9077b82..34657aa8 100644
--- a/examples/hotelling_law/hotelling_law/agents.py
+++ b/examples/hotelling_law/hotelling_law/agents.py
@@ -9,7 +9,7 @@ class StoreAgent(CellAgent):
     """An agent representing a store with a price and ability to move
     and adjust prices."""
 
-    def __init__(self, model, price=10, can_move=True, strategy="Budget"):
+    def __init__(self, model, cell, price=10, can_move=True, strategy="Budget"):
         # Initializes the store agent with a unique ID,
         # the model it belongs to,its initial price,
         # and whether it can move.
@@ -20,6 +20,7 @@ def __init__(self, model, price=10, can_move=True, strategy="Budget"):
         self.previous_market_share = 0  # Initialize previous market share
         self.strategy = strategy  # Store can be low cost (Budget)
         # / differential (Premium)
+        self.cell = cell
 
     def estimate_market_share(self, new_position=None):
         position = new_position if new_position else self.cell
@@ -157,12 +158,13 @@ class ConsumerAgent(CellAgent):
     """A consumer agent that chooses a store
     based on price and distance."""
 
-    def __init__(self, model):
+    def __init__(self, model, cell, consumer_preferences):
         super().__init__(model)
         self.preferred_store = None
+        self.cell = cell
+        self.preference = consumer_preferences
 
     def determine_preferred_store(self):
-        consumer_preference = self.model.agents_by_type[ConsumerAgent]
         stores = self.model.agents_by_type[StoreAgent]
 
         if len(stores) == 0:  # Check if the stores AgentSet is empty
@@ -173,11 +175,11 @@ def determine_preferred_store(self):
 
         for store in stores:
             # Calculate score based on consumer preference
-            if consumer_preference == "proximity":
+            if self.preference == "proximity":
                 score = self.euclidean_distance(
                     self.cell.coordinate, store.cell.coordinate
                 )
-            elif consumer_preference == "price":
+            elif self.preference == "price":
                 score = store.price
             else:  # Default case includes both proximity and price
                 score = store.price + self.euclidean_distance(
diff --git a/examples/hotelling_law/hotelling_law/model.py b/examples/hotelling_law/hotelling_law/model.py
index e6e7f5ef..cc2bdc0a 100644
--- a/examples/hotelling_law/hotelling_law/model.py
+++ b/examples/hotelling_law/hotelling_law/model.py
@@ -186,22 +186,20 @@ def _initialize_agents(self):
             if can_move:
                 mobile_agents_assigned += 1
 
-            agent = StoreAgent(self, can_move=can_move, strategy=strategy)
-
-            # Randomly place agents on the grid for a grid environment.
-            x = self.random.randrange(self.grid.dimensions[0])
-            y = self.random.randrange(self.grid.dimensions[1])
-            agent.cell = self.grid[(x, y)]
+            StoreAgent(
+                self,
+                self.grid.all_cells.select_random_cell(),
+                can_move=can_move,
+                strategy=strategy,
+            )
 
         # Place consumer agents
         for _ in range(self.num_consumers):
-            # Ensure unique ID across all agents
-            consumer = ConsumerAgent(self)
-
-            # Place consumer randomly on the grid
-            x = self.random.randrange(self.grid.dimensions[0])
-            y = self.random.randrange(self.grid.dimensions[1])
-            consumer.cell = self.grid[(x, y)]
+            ConsumerAgent(
+                self,
+                self.grid.all_cells.select_random_cell(),
+                self.consumer_preferences,
+            )
 
     # Method to advance the simulation by one step.
     def step(self):