Implement best first local search algorithm

src/processing.py

@@ -72,6 +72,17 @@ def local_search(n, m, data):
     for _ in range(m):
         pass
     return solutions
+def get_random_solution(previous, data):
+    solution = previous.copy()
+    worst_index = previous["distance"].astype(float).idxmin()
+    random_candidate = data.loc[randint(low=0, high=len(data.index))]
+    while (
+        solution.loc[worst_index, "distance"] <= previous.loc[worst_index, "distance"]
+    ):
+        solution.loc[worst_index] = random_candidate
+    return solution
+
+
 
 
 def execute_algorithm(choice, n, m, data):