maggicl
/
AICup
Archived
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

run

This commit is contained in:
UmbertoJr 2019-12-02 09:11:15 +01:00
parent 94ab290de2
commit b8b4840408
1 changed files with 24 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

35
run.py
View File

@ -2,6 +2,23 @@ from src import *
import pandas as pd
def add(solver, instance, improve, index, results, name, verbose, show_plots):
solver.bind(improve)
solver(instance, return_value=False, verbose=verbose)
if verbose:
print(f"the total length for the solution found is {solver.found_length}",
f"while the optimal length is {instance.best_sol}",
f"the gap is {solver.gap}%",
f"the solution is found in {solver.time_to_solve} seconds", sep="\n")
index.append((name, solver.name_method))
results.append([solver.found_length, instance.best_sol, solver.gap, solver.time_to_solve])
if show_plots:
solver.plot_solution()
def run(show_plots=False, verbose=False):
# names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_]
names = ["eil76.tsp"]
@ -21,20 +38,16 @@ def run(show_plots=False, verbose=False):
for init in initializers:
for improve in improvements:
solver = Solver_TSP(init)
solver.bind(improve)
solver(instance, return_value=False, verbose=verbose)
add(solver, instance, improve, index, results, name, verbose, show_plots)
for improve2 in [j for j in improvements if j not in [improve]]:
add(solver, instance, improve2, index, results, name, verbose, show_plots)
if verbose:
print(f"the total length for the solution found is {solver.found_length}",
f"while the optimal length is {instance.best_sol}",
f"the gap is {solver.gap}%",
f"the solution is found in {solver.time_to_solve} seconds", sep="\n")
for improve3 in [j for j in improvements if j not in [improve, improve2]]:
add(solver, instance, improve3, index, results, name, verbose, show_plots)
solver.pop()
index.append((name, solver.name_method))
results.append([solver.found_length, instance.best_sol, solver.gap, solver.time_to_solve])
solver.pop()
if show_plots:
solver.plot_solution()
if instance.exist_opt and show_plots:
solver.solution = np.concatenate([instance.optimal_tour, [instance.optimal_tour[0]]])