Implement element evaluation

src/genetic_algorithm.py

@@ -1,3 +1,4 @@
+from numpy import put, sum, append, where, zeros
 from numpy.random import choice, seed
 
 
@@ -9,6 +10,17 @@ def get_first_random_solution(n, m):
     return solution
 
 
+def evaluate_element(element, data):
+    fitness = []
+    genotype = where(element == True)
+    indexes = genotype[0]
+    distances = data.query(f"source in @indexes and destination in @indexes")
+    for item in indexes[:-1]:
+        element_df = distances.query(f"source == {item} or destination == {item}")
+        max_distance = element_df["distance"].astype(float).max()
+        fitness = append(arr=fitness, values=max_distance)
+        distances = distances.query(f"source != {item} and destination != {item}")
+    return sum(fitness)
 
 
 def element_in_dataframe(solution, element):