local
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3 changed files with 73 additions and 61 deletions
1
run.py
1
run.py
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@ -23,7 +23,6 @@ def run(show_plots=False, verbose=False):
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solver = Solver_TSP(init)
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for improve in improvements:
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solver.bind(improve)
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end - start
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solver(instance, return_value=False, verbose=verbose)
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if verbose:
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@ -46,6 +46,7 @@ class Solver_TSP:
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print("init ok")
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for i in range(1, len(self.methods)):
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self.solution = self.available_improvements[self.methods[i]](self.solution, self.instance)
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print(len(self.solution))
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assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid"
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print("improve ok")
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@ -1,5 +1,6 @@
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import os
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import numpy as np
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if 'AI' in os.getcwd():
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from src.utils import *
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else:
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@ -65,7 +66,8 @@ class TwoOpt:
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else:
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return new_tsp_sequence.tolist(), new_len, uncross
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return new_tsp_sequence.tolist(), new_len, uncross
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# return new_tsp_sequence.tolist(), new_len, uncross
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return new_tsp_sequence.tolist()
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class TwoDotFiveOpt:
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@ -86,15 +88,16 @@ class TwoDotFiveOpt:
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for j in range(i + 1, seq_length):
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# 2opt swap
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twoOpt_tsp_sequence = TwoOpt.swap2opt(tsp_sequence, i, j)
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twoOpt_len = distance + TwoOpt.gain(i, j , tsp_sequence, matrix_dist)
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twoOpt_len = distance + TwoOpt.gain(i, j, tsp_sequence, matrix_dist)
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# node shift 1
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first_shift_tsp_sequence = TwoDotFiveOpt.shift1(tsp_sequence, i,j)
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first_shift_len = distance + TwoDotFiveOpt.shift_gain1(i,j, tsp_sequence, matrix_dist)
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first_shift_tsp_sequence = TwoDotFiveOpt.shift1(tsp_sequence, i, j)
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first_shift_len = distance + TwoDotFiveOpt.shift_gain1(i, j, tsp_sequence, matrix_dist)
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# node shift 2
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second_shift_tsp_sequence = TwoDotFiveOpt.shift2(tsp_sequence, i,j)
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second_shift_len = distance + TwoDotFiveOpt.shift_gain2(i,j, tsp_sequence, matrix_dist)
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second_shift_tsp_sequence = TwoDotFiveOpt.shift2(tsp_sequence, i, j)
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second_shift_len = distance + TwoDotFiveOpt.shift_gain2(i, j, tsp_sequence, matrix_dist)
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best_len, best_method = min([twoOpt_len, first_shift_len, second_shift_len]), np.argmin([twoOpt_len, first_shift_len, second_shift_len])
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best_len, best_method = min([twoOpt_len, first_shift_len, second_shift_len]), np.argmin(
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[twoOpt_len, first_shift_len, second_shift_len])
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sequences = [twoOpt_tsp_sequence, first_shift_tsp_sequence, second_shift_tsp_sequence]
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if best_len < distance:
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uncrosses += 1
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@ -105,28 +108,36 @@ class TwoDotFiveOpt:
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@staticmethod
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def shift1(tsp_sequence, i, j):
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new_tsp_sequence = np.concatenate([tsp_sequence[:i], tsp_sequence[i+1: j+1], [tsp_sequence[i]], tsp_sequence[j+1:]])
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new_tsp_sequence = np.concatenate(
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[tsp_sequence[:i], tsp_sequence[i + 1: j + 1], [tsp_sequence[i]], tsp_sequence[j + 1:]])
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return new_tsp_sequence
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@staticmethod
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def shift_gain1(i, j , tsp_sequence, matrix_dist):
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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]])
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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]])
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def shift_gain1(i, j, tsp_sequence, matrix_dist):
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old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]] + matrix_dist[
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tsp_sequence[i], tsp_sequence[i + 1]] + matrix_dist[tsp_sequence[j], tsp_sequence[j + 1]])
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changed_links_len = (matrix_dist[tsp_sequence[i - 1], tsp_sequence[i + 1]] + matrix_dist[
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tsp_sequence[i], tsp_sequence[j]] + matrix_dist[tsp_sequence[i], tsp_sequence[j + 1]])
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return - old_link_len + changed_links_len
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@staticmethod
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def shift2(tsp_sequence, i, j):
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new_tsp_sequence = np.concatenate([tsp_sequence[:i], [tsp_sequence[j]], tsp_sequence[i: j], tsp_sequence[j+1:]])
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new_tsp_sequence = np.concatenate(
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[tsp_sequence[:i], [tsp_sequence[j]], tsp_sequence[i: j], tsp_sequence[j + 1:]])
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return new_tsp_sequence
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@staticmethod
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def shift_gain2(i, j , tsp_sequence, matrix_dist):
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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]])
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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]])
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def shift_gain2(i, j, tsp_sequence, matrix_dist):
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old_link_len = (matrix_dist[tsp_sequence[i], tsp_sequence[i - 1]] + matrix_dist[
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tsp_sequence[j], tsp_sequence[j - 1]] + matrix_dist[tsp_sequence[j], tsp_sequence[j + 1]])
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changed_links_len = (
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matrix_dist[tsp_sequence[j], tsp_sequence[i - 1]] + matrix_dist[tsp_sequence[i], tsp_sequence[j]] +
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matrix_dist[tsp_sequence[j - 1], tsp_sequence[j + 1]])
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return - old_link_len + changed_links_len
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@staticmethod
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def loop2dot5opt(solution, instance, max_num_of_changes=400): # Iterate stoep2opt max_iter times (2-opt local search)
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def loop2dot5opt(solution, instance,
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max_num_of_changes=400): # Iterate stoep2opt max_iter times (2-opt local search)
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"""
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@param solution:
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@ -146,5 +157,6 @@ class TwoDotFiveOpt:
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actual_len = new_len
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else:
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return new_tsp_sequence.tolist(), actual_len, uncross
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return new_tsp_sequence.tolist(), actual_len, uncross
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# return new_tsp_sequence.tolist(), actual_len, uncross
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return new_tsp_sequence.tolist()
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