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solver

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This commit is contained in:
UmbertoJr 2019-11-18 08:15:29 +01:00
parent 2923872054
commit 00c1eb8511
2 changed files with 22 additions and 17 deletions
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31
run.py
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@ -6,7 +6,8 @@ from time import time as t
def run(show_plots=False, verbose=False): def run(show_plots=False, verbose=False):
# names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_] # names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_]
names = ["eil76.tsp", "kroA100.tsp"] names = ["eil76.tsp", "kroA100.tsp"]
methods = Solver_TSP.available_methods.keys() initializers = Solver_TSP.available_initializers.keys()
improvements = Solver_TSP.available_improvements.keys()
results = [] results = []
index = [] index = []
for name in names: for name in names:
@ -18,23 +19,23 @@ def run(show_plots=False, verbose=False):
if show_plots: if show_plots:
instance.plot_data() instance.plot_data()
for method in methods: for init in initializers:
solver = Solver_TSP(method) solver = Solver_TSP(init)
start = t() for improve in improvements:
solver(instance, return_value=False, verbose=verbose) solver.bind(improve)
end = t() solver(instance, return_value=False, verbose=verbose)
if verbose: if verbose:
print(f"the total length for the solution found is {solver.found_length}", print(f"the total length for the solution found is {solver.found_length}",
f"while the optimal length is {instance.best_sol}", f"while the optimal length is {instance.best_sol}",
f"the gap is {solver.gap}%", f"the gap is {solver.gap}%",
f"the solution is found in {np.round(end - start, 5)} seconds", sep="\n") f"the solution is found in {solver.time_to_solve} seconds", sep="\n")
index.append((name, method)) index.append((name, solver.name_method))
results.append([solver.found_length, instance.best_sol, solver.gap, end - start]) results.append([solver.found_length, instance.best_sol, solver.gap, solver.time_to_solve])
if show_plots: if show_plots:
solver.plot_solution() solver.plot_solution()
if instance.exist_opt: if instance.exist_opt:
solver.solution = np.concatenate([instance.optimal_tour, [instance.optimal_tour[0]]]) solver.solution = np.concatenate([instance.optimal_tour, [instance.optimal_tour[0]]])

8
src/TSP_solver.py
View file

@ -1,6 +1,7 @@
from numpy.core._multiarray_umath import ndarray from numpy.core._multiarray_umath import ndarray
import os import os
from time import time as t from time import time as t
import numpy as np
if 'AI' in os.getcwd(): if 'AI' in os.getcwd():
from src import * from src import *
else: else:
@ -25,12 +26,14 @@ class Solver_TSP:
# "best_nn": self.best_nn, "multi_fragment": self.mf} # "best_nn": self.best_nn, "multi_fragment": self.mf}
self.initializer = initializer self.initializer = initializer
self.methods = [initializer] self.methods = [initializer]
self.name_method = "initialize with " + initializer
self.solved = False self.solved = False
assert initializer in self.available_initializers, f"the {initializer} initializer is not available currently." assert initializer in self.available_initializers, f"the {initializer} initializer is not available currently."
def bind(self, local_or_meta): def bind(self, local_or_meta):
assert local_or_meta in self.available_improvements, f"the {local_or_meta} method is not available currently." assert local_or_meta in self.available_improvements, f"the {local_or_meta} method is not available currently."
self.methods.append(local_or_meta) self.methods.append(local_or_meta)
self.name_method = ", improve with " + local_or_meta
def __call__(self, instance_, verbose=True, return_value=True): def __call__(self, instance_, verbose=True, return_value=True):
self.instance = instance_ self.instance = instance_
@ -45,10 +48,11 @@ class Solver_TSP:
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"
end = t() end = t()
self.time_to_solve = np.around(end - start,3)
self.evaluate_solution() self.evaluate_solution()
self._gap() self._gap()
if verbose: if verbose:
print(f"### solution found with {self.gap} % gap in {np.around(end - start, 3)} seconds ####") print(f"### solution found with {self.gap} % gap in {self.time_to_solve} seconds ####")
if return_value: if return_value:
return self.solution return self.solution
@ -56,7 +60,7 @@ class Solver_TSP:
assert self.solved, "You can't plot the solution, you need to solve it first!" assert self.solved, "You can't plot the solution, you need to solve it first!"
plt.figure(figsize=(8, 8)) plt.figure(figsize=(8, 8))
self._gap() self._gap()
plt.title(f"{self.instance.name} solved with {self.method} solver, gap {self.gap}") plt.title(f"{self.instance.name} solved with {self.name_method} solver, gap {self.gap}")
ordered_points = self.instance.points[self.solution] ordered_points = self.instance.points[self.solution]
plt.plot(ordered_points[:, 1], ordered_points[:, 2], 'b-') plt.plot(ordered_points[:, 1], ordered_points[:, 2], 'b-')
plt.show() plt.show()