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Only insert element that are not duplicated

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coolneng 2021-04-19 15:51:12 +02:00
parent 5e6a6d00e9
commit 2eb84a6883
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
1 changed files with 6 additions and 9 deletions
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15
src/local_search.py
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@ -3,14 +3,17 @@ from numpy.random import choice, seed
def get_first_random_solution(m, data): def get_first_random_solution(m, data):
seed(42) seed(42)
random_indexes = choice(len(data.index), size=m) random_indexes = choice(len(data.index), size=m, replace=False)
return data.iloc[random_indexes] return data.loc[random_indexes]
def replace_worst_element(previous, data): def replace_worst_element(previous, data):
solution = previous.copy() solution = previous.copy()
worst_index = solution["distance"].astype(float).idxmin() worst_index = solution["distance"].astype(float).idxmin()
solution.loc[worst_index] = data.sample(random_state=42).squeeze() random_element = data.sample().squeeze()
while solution.isin(random_element.values.ravel()).any().any():
random_element = data.sample().squeeze()
solution.loc[worst_index] = random_element
return solution, worst_index return solution, worst_index
@ -28,11 +31,6 @@ def get_random_solution(previous, data):
return solution return solution
def remove_duplicates(element, data):
duplicate_free_df = data.query(
"(source not in @element.source) or (destination not in @element.destination)"
)
return duplicate_free_df
def explore_neighbourhood(element, data, max_iterations=100000): def explore_neighbourhood(element, data, max_iterations=100000):
@ -41,7 +39,6 @@ def explore_neighbourhood(element, data, max_iterations=100000):
for _ in range(max_iterations): for _ in range(max_iterations):
previous_solution = neighbourhood[-1] previous_solution = neighbourhood[-1]
neighbour = get_random_solution(previous=previous_solution, data=data) neighbour = get_random_solution(previous=previous_solution, data=data)
data = remove_duplicates(element=neighbour, data=data)
if neighbour.equals(previous_solution): if neighbour.equals(previous_solution):
break break
neighbourhood.append(neighbour) neighbourhood.append(neighbour)