local search

This commit is contained in:
UmbertoJr 2019-11-18 06:57:19 +01:00
parent 35b51416c1
commit b094d8190c
1 changed files with 69 additions and 0 deletions

69
src/local_search.py Normal file
View File

@ -0,0 +1,69 @@
import os
if 'AI' in os.getcwd():
from src.utils import *
else:
from AI2019.src.utils import *
class TwoOpt:
@staticmethod
def step2opt(solution, matrix_dist, distance):
"""
One step of 2opt, one double loop and return first improved sequence
@param tsp_sequence:
@param matrix_dist:
@param distance:
@return:
"""
seq_length = len(solution) - 1
tsp_sequence = np.array(solution)
uncrosses = 0
for i in range(1, seq_length - 1):
for j in range(i + 1, seq_length):
new_tsp_sequence = TwoOpt.swap2opt(tsp_sequence, i, j)
new_distance = distance + TwoOpt.gain(i, j, tsp_sequence, matrix_dist)
if new_distance < distance:
uncrosses += 1
tsp_sequence = np.copy(new_tsp_sequence)
distance = new_distance
return tsp_sequence, distance, uncrosses
@staticmethod
def swap2opt(tsp_sequence, i, j):
new_tsp_sequence = np.copy(tsp_sequence)
new_tsp_sequence[i:j + 1] = np.flip(tsp_sequence[i:j + 1], axis=0) # flip or swap ?
return new_tsp_sequence
@staticmethod
def gain(i, j, tsp_sequence, matrix_dist):
old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]] + matrix_dist[
tsp_sequence[j], tsp_sequence[j + 1]])
changed_links_len = (matrix_dist[tsp_sequence[j], tsp_sequence[i - 1]] + matrix_dist[
tsp_sequence[i], tsp_sequence[j + 1]])
return - old_link_len + changed_links_len
@staticmethod
def loop2opt(solution, instance, max_num_of_uncrosses=400): # Iterate step2opt max_iter times (2-opt local search)
"""
@param tsp_sequence:
@param instance:
@param max_num_of_uncrosses:
@return:
"""
matrix_dist = instance.dist_matrix
new_len = compute_lenght(solution, matrix_dist)
new_tsp_sequence = np.copy(np.array(solution))
uncross = 0
while uncross < max_num_of_uncrosses:
new_tsp_sequence, new_reward, uncr_ = TwoOpt.step2opt(new_tsp_sequence, matrix_dist, new_len)
uncross += uncr_
if new_reward < new_len:
new_len = new_reward
else:
return new_tsp_sequence.tolist(), new_len, uncross
return new_tsp_sequence.tolist(), new_len, uncross