Return the best solution when you can't explore

src/local_search.py

@@ -17,26 +17,35 @@ def replace_worst_element(previous, data):
     return solution, worst_index
 
 
+def choose_best_solution(previous, current, index):
+    if previous.loc[index].distance >= current.loc[index].distance:
+        return previous
+    return current
+
+
 def get_random_solution(previous, data):
     candidates = []
     candidates.append(previous)
     solution, worst_index = replace_worst_element(previous, data)
     previous_worst_distance = previous["distance"].loc[worst_index]
-    while candidates[-1].distance.loc[worst_index] <= previous_worst_distance:
     last_solution = candidates[-1]
+    while last_solution.distance.loc[worst_index] <= previous_worst_distance:
         solution, _ = replace_worst_element(previous=solution, data=data)
         if solution.equals(last_solution):
-            return last_solution
+            best_solution = choose_best_solution(
+                previous=previous, current=solution, index=worst_index
+            )
+            return best_solution
         candidates.append(solution)
-    return solution
+        last_solution = candidates[-1]
-
+    return last_solution
-
 
 
 def explore_neighbourhood(element, data, max_iterations=100000):
     neighbourhood = []
     neighbourhood.append(element)
-    for _ in range(max_iterations):
+    for i in range(max_iterations):
+        print(f"Iteration {i}")
         previous_solution = neighbourhood[-1]
         neighbour = get_random_solution(previous=previous_solution, data=data)
         if neighbour.equals(previous_solution):