solver
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parent
2923872054
commit
00c1eb8511
2 changed files with 22 additions and 17 deletions
31
run.py
31
run.py
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@ -6,7 +6,8 @@ from time import time as t
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def run(show_plots=False, verbose=False):
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# names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_]
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names = ["eil76.tsp", "kroA100.tsp"]
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methods = Solver_TSP.available_methods.keys()
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initializers = Solver_TSP.available_initializers.keys()
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improvements = Solver_TSP.available_improvements.keys()
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results = []
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index = []
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for name in names:
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@ -18,23 +19,23 @@ def run(show_plots=False, verbose=False):
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if show_plots:
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instance.plot_data()
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for method in methods:
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solver = Solver_TSP(method)
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start = t()
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solver(instance, return_value=False, verbose=verbose)
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end = t()
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for init in initializers:
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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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solver(instance, return_value=False, verbose=verbose)
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if verbose:
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print(f"the total length for the solution found is {solver.found_length}",
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f"while the optimal length is {instance.best_sol}",
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f"the gap is {solver.gap}%",
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f"the solution is found in {np.round(end - start, 5)} seconds", sep="\n")
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if verbose:
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print(f"the total length for the solution found is {solver.found_length}",
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f"while the optimal length is {instance.best_sol}",
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f"the gap is {solver.gap}%",
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f"the solution is found in {solver.time_to_solve} seconds", sep="\n")
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index.append((name, method))
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results.append([solver.found_length, instance.best_sol, solver.gap, end - start])
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index.append((name, solver.name_method))
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results.append([solver.found_length, instance.best_sol, solver.gap, solver.time_to_solve])
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if show_plots:
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solver.plot_solution()
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if show_plots:
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solver.plot_solution()
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if instance.exist_opt:
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solver.solution = np.concatenate([instance.optimal_tour, [instance.optimal_tour[0]]])
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@ -1,6 +1,7 @@
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from numpy.core._multiarray_umath import ndarray
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import os
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from time import time as t
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import numpy as np
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if 'AI' in os.getcwd():
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from src import *
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else:
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@ -25,12 +26,14 @@ class Solver_TSP:
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# "best_nn": self.best_nn, "multi_fragment": self.mf}
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self.initializer = initializer
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self.methods = [initializer]
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self.name_method = "initialize with " + initializer
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self.solved = False
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assert initializer in self.available_initializers, f"the {initializer} initializer is not available currently."
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def bind(self, local_or_meta):
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assert local_or_meta in self.available_improvements, f"the {local_or_meta} method is not available currently."
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self.methods.append(local_or_meta)
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self.name_method = ", improve with " + local_or_meta
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def __call__(self, instance_, verbose=True, return_value=True):
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self.instance = instance_
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@ -45,10 +48,11 @@ class Solver_TSP:
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assert self.check_if_solution_is_valid(self.solution), "Error the solution is not valid"
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end = t()
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self.time_to_solve = np.around(end - start,3)
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self.evaluate_solution()
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self._gap()
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if verbose:
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print(f"### solution found with {self.gap} % gap in {np.around(end - start, 3)} seconds ####")
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print(f"### solution found with {self.gap} % gap in {self.time_to_solve} seconds ####")
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if return_value:
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return self.solution
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@ -56,7 +60,7 @@ class Solver_TSP:
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assert self.solved, "You can't plot the solution, you need to solve it first!"
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plt.figure(figsize=(8, 8))
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self._gap()
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plt.title(f"{self.instance.name} solved with {self.method} solver, gap {self.gap}")
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plt.title(f"{self.instance.name} solved with {self.name_method} solver, gap {self.gap}")
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ordered_points = self.instance.points[self.solution]
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plt.plot(ordered_points[:, 1], ordered_points[:, 2], 'b-')
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plt.show()
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