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This commit is contained in:
UmbertoJr 2019-11-18 08:21:05 +01:00
parent d29a162276
commit 2e9910d324
3 changed files with 73 additions and 61 deletions
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1
run.py
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@ -23,7 +23,6 @@ def run(show_plots=False, verbose=False):
solver = Solver_TSP(init) solver = Solver_TSP(init)
for improve in improvements: for improve in improvements:
solver.bind(improve) solver.bind(improve)
end - start
solver(instance, return_value=False, verbose=verbose) solver(instance, return_value=False, verbose=verbose)
if verbose: if verbose:

1
src/TSP_solver.py
View file

@ -46,6 +46,7 @@ class Solver_TSP:
print("init ok") print("init ok")
for i in range(1, len(self.methods)): for i in range(1, len(self.methods)):
self.solution = self.available_improvements[self.methods[i]](self.solution, self.instance) self.solution = self.available_improvements[self.methods[i]](self.solution, self.instance)
print(len(self.solution))
assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid" assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid"
print("improve ok") print("improve ok")

32
src/local_search.py
View file

@ -1,5 +1,6 @@
import os import os
import numpy as np import numpy as np
if 'AI' in os.getcwd(): if 'AI' in os.getcwd():
from src.utils import * from src.utils import *
else: else:
@ -65,7 +66,8 @@ class TwoOpt:
else: else:
return new_tsp_sequence.tolist(), new_len, uncross return new_tsp_sequence.tolist(), new_len, uncross
return new_tsp_sequence.tolist(), new_len, uncross # return new_tsp_sequence.tolist(), new_len, uncross
return new_tsp_sequence.tolist()
class TwoDotFiveOpt: class TwoDotFiveOpt:
@ -94,7 +96,8 @@ class TwoDotFiveOpt:
second_shift_tsp_sequence = TwoDotFiveOpt.shift2(tsp_sequence, i, j) second_shift_tsp_sequence = TwoDotFiveOpt.shift2(tsp_sequence, i, j)
second_shift_len = distance + TwoDotFiveOpt.shift_gain2(i, j, tsp_sequence, matrix_dist) second_shift_len = distance + TwoDotFiveOpt.shift_gain2(i, j, tsp_sequence, matrix_dist)
best_len, best_method = min([twoOpt_len, first_shift_len, second_shift_len]), np.argmin([twoOpt_len, first_shift_len, second_shift_len]) best_len, best_method = min([twoOpt_len, first_shift_len, second_shift_len]), np.argmin(
[twoOpt_len, first_shift_len, second_shift_len])
sequences = [twoOpt_tsp_sequence, first_shift_tsp_sequence, second_shift_tsp_sequence] sequences = [twoOpt_tsp_sequence, first_shift_tsp_sequence, second_shift_tsp_sequence]
if best_len < distance: if best_len < distance:
uncrosses += 1 uncrosses += 1
@ -105,28 +108,36 @@ class TwoDotFiveOpt:
@staticmethod @staticmethod
def shift1(tsp_sequence, i, j): def shift1(tsp_sequence, i, j):
new_tsp_sequence = np.concatenate([tsp_sequence[:i], tsp_sequence[i+1: j+1], [tsp_sequence[i]], tsp_sequence[j+1:]]) new_tsp_sequence = np.concatenate(
[tsp_sequence[:i], tsp_sequence[i + 1: j + 1], [tsp_sequence[i]], tsp_sequence[j + 1:]])
return new_tsp_sequence return new_tsp_sequence
@staticmethod @staticmethod
def shift_gain1(i, j, tsp_sequence, matrix_dist): def shift_gain1(i, j, tsp_sequence, matrix_dist):
old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]]+ matrix_dist[tsp_sequence[i], tsp_sequence[i + 1]] + matrix_dist[tsp_sequence[j], tsp_sequence[j + 1]]) old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]] + matrix_dist[
changed_links_len = (matrix_dist[tsp_sequence[i - 1], tsp_sequence[i + 1]] + matrix_dist[tsp_sequence[i], tsp_sequence[j]] + matrix_dist[tsp_sequence[i], tsp_sequence[j + 1]]) tsp_sequence[i], tsp_sequence[i + 1]] + matrix_dist[tsp_sequence[j], tsp_sequence[j + 1]])
changed_links_len = (matrix_dist[tsp_sequence[i - 1], tsp_sequence[i + 1]] + matrix_dist[
tsp_sequence[i], tsp_sequence[j]] + matrix_dist[tsp_sequence[i], tsp_sequence[j + 1]])
return - old_link_len + changed_links_len return - old_link_len + changed_links_len
@staticmethod @staticmethod
def shift2(tsp_sequence, i, j): def shift2(tsp_sequence, i, j):
new_tsp_sequence = np.concatenate([tsp_sequence[:i], [tsp_sequence[j]], tsp_sequence[i: j], tsp_sequence[j+1:]]) new_tsp_sequence = np.concatenate(
[tsp_sequence[:i], [tsp_sequence[j]], tsp_sequence[i: j], tsp_sequence[j + 1:]])
return new_tsp_sequence return new_tsp_sequence
@staticmethod @staticmethod
def shift_gain2(i, j, tsp_sequence, matrix_dist): def shift_gain2(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]] + matrix_dist[tsp_sequence[j], tsp_sequence[j + 1]]) old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]] + matrix_dist[
changed_links_len = (matrix_dist[tsp_sequence[j], tsp_sequence[i - 1]] + matrix_dist[tsp_sequence[i], tsp_sequence[j]] + matrix_dist[tsp_sequence[j - 1], tsp_sequence[j + 1]]) tsp_sequence[j], tsp_sequence[j - 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]] +
matrix_dist[tsp_sequence[j - 1], tsp_sequence[j + 1]])
return - old_link_len + changed_links_len return - old_link_len + changed_links_len
@staticmethod @staticmethod
def loop2dot5opt(solution, instance, max_num_of_changes=400): # Iterate stoep2opt max_iter times (2-opt local search) def loop2dot5opt(solution, instance,
max_num_of_changes=400): # Iterate stoep2opt max_iter times (2-opt local search)
""" """
@param solution: @param solution:
@ -146,5 +157,6 @@ class TwoDotFiveOpt:
actual_len = new_len actual_len = new_len
else: else:
return new_tsp_sequence.tolist(), actual_len, uncross return new_tsp_sequence.tolist(), actual_len, uncross
return new_tsp_sequence.tolist(), actual_len, uncross
# return new_tsp_sequence.tolist(), actual_len, uncross
return new_tsp_sequence.tolist()