Update app.py

app.py

@@ -62,18 +62,15 @@ def optimize_dishes_for_budget(city, daily_budget):
     calories = [nutritional_data[dish]["Energy (kcal)"] for dish in nutritional_data]
     proteins = [nutritional_data[dish]["Protein (g)"] for dish in nutritional_data]
     
-    # Introduce a small penalty for selecting large quantities of any single dish
-    diversity_penalty = np.ones(len(costs)) * 0.01
-
-    # Objective function: Maximize nutritional value (calories + protein) while encouraging diversity
-    c = [-1 * (cal + prot) + penalty for cal, prot, penalty in zip(calories, proteins, diversity_penalty)]
+    # Objective function: Maximize nutritional value (calories + protein)
+    c = [-1 * (cal + prot) for cal, prot in zip(calories, proteins)]  # Minimize negative of nutrition for maximization
     
     # Constraint: Total cost must not exceed the daily budget
     A_ub = [costs]  # Sum of costs * portions <= daily_budget
     b_ub = [daily_budget]
     
     # Bounds for each dish (x >= 0)
-    bounds = [(0, None) for _ in costs]
+    bounds = [(0.1, None) for _ in costs]  # Minimum 0.1 portion to encourage diversity
 
     # Solve the optimization problem
     result = linprog(c, A_ub=A_ub, b_ub=b_ub, bounds=bounds, method='highs')