# -*- coding: utf-8 -*-
###############################################################################
""" Tries to be as fast as possible in solving TSPs as possible using Gurobi
and LKH as experimentally it was found out to be time-optimal."""
###############################################################################
from tsp_solvers.tsp_solver_ropt import solve_tsp_ropt
from tsp_solvers.tsp_solver_lkh import solve_tsp_lkh
from tsp_solvers.tsp_solver_gurobi import solve_tsp_gurobi
def solve_tsp_fast(D, selected_idxs):
if len(selected_idxs)<5:
return solve_tsp_ropt(D, selected_idxs)
elif len(selected_idxs)<20:
return solve_tsp_gurobi(D, selected_idxs)
else:
return solve_tsp_lkh(D, selected_idxs, num_runs=1)
if __name__=="__main__":
from shared_cli import tsp_cli
tsp_cli("fast", solve_tsp_fast)
skip = True
elif "Length = " in l:
obj_f = float(l.split()[-1])
elif not skip:
vrp_nid = selected_idxs[int(l)-1]
if vrp_nid==0:
tail.append(0)
depot_found = True
if depot_found:
sol.append(vrp_nid)
else:
tail.append(vrp_nid)
if l == "TOUR_SECTION":
skip = False
sol+=tail
if not depot_found:
sol+=[sol[0]]
remove_file(temp_problem_file_path)
remove_file(temp_parameter_file_path)
remove_file(temp_output_file_path)
if are_float_distances:
obj_f = obj_f/float_accuracy;
return sol, obj_f
if __name__=="__main__":
from shared_cli import tsp_cli
tsp_cli("lkh", solve_tsp_lkh)
m.setParam('TimeLimit', MAX_MIP_SOLVER_RUNTIME)
m.setParam('Threads', MIP_SOLVER_THREADS)
m.optimize(_subtourelim)
# restore SIGINT callback handler which is changed by gurobipy
signal(SIGINT, default_int_handler)
status = m.Status
if status == GRB.TIME_LIMIT:
raise GurobiError(
10023, "Gurobi timeout reached when attempting to solve TSP")
elif m.Status == GRB.INTERRUPTED:
raise KeyboardInterrupt()
solution = m.getAttr('x', edgevars)
selected = [(i, j) for i in range(n) for j in range(n)
if solution[i, j] > 0.5]
cycles = _subtour(selected, n)
assert len(cycles) == n
# make the route always start from the 1st index
sol = [selected_idxs[i] for i in cycles] + [selected_idxs[0]]
obj_f = m.objVal
return sol, obj_f
if __name__ == "__main__":
from shared_cli import tsp_cli
tsp_cli("gurobi", solve_tsp_gurobi)
sol = None
sol_f = None
best_re = re.compile("try [0-9]+, Best ([0-9]+(\.?[0-9]*)?),")
best_obj = None
for l in stdout_data.split('\n'):
if "best solution so far is" in l[:25]:
tour_indices = [
int(n)
for n in l.replace("best solution so far is", "").split()
]
sol = list(selected_idxs[i] for i in tour_indices)
first_pos = sol.index(selected_idxs[0])
sol = sol[first_pos:] + sol[:first_pos] + [selected_idxs[0]]
sol_f = sum(D[sol[i - 1]][sol[i]] for i in range(1, len(sol)))
#print("REMOVEME:", sol_f, best_obj)
bo = best_re.search(l)
if bo:
best_obj = float(bo.group(1))
if are_float_distances:
best_obj = best_obj / float_accuracy
remove_file(temp_problem_file_path)
return sol, sol_f
if __name__ == "__main__":
from shared_cli import tsp_cli
tsp_cli("acotsp", solve_tsp_acotsp)
# make first 2-optimal
if do2opt:
improved = True
while improved:
improved = False
improved_route, delta = do_2opt_move(new_route, D, 1)
if improved_route is not None:
new_route = improved_route
new_route_cost += delta
improved = True
# then 3-optimal (do not waste time on "easy" 2-opt
# operations if the route has already been made 2-optimal
if do3opt:
improved = True
while improved:
improved = False
improved_route, delta = do_3opt_move(new_route, D, 1)
if improved_route is not None:
new_route = improved_route
new_route_cost += delta
improved = True
return new_route, new_route_cost
if __name__ == "__main__":
from shared_cli import tsp_cli
tsp_cli("ropt", solve_tsp_ropt)