def setUp(self):
raw_data = dm.Importer()
#raw_data.import_data("./tests/cvrp2.test")
#raw_data.import_data("./tests/ulysses-n16-k3.vrp")
#raw_data.import_data("./tests/E-n23-k3.vrp")
#raw_data.import_data("./tests/cvrp3.test")
#raw_data.import_data("./tests/P-n19-k2.vrp")
raw_data.import_data("./tests/cvrp4.test")
data = dm.DataMapper(raw_data)
self.instance = i.ProblemInstance(data)
# self.instance.distance_matrix = [
# [0, 6, 3, 1, 7, 1],
# [6, 0, 1, 9, 6, 3],
# [3, 5, 0, 8, 1, 4],
# [1, 9, 8, 0, 9, 9],
# [1, 9, 2, 9, 0, 9],
# [11,1, 4, 9, 3, 0]
# ]
self.solution = a.Solution(self.instance)
greedy = gf.GreedyFirst(self.solution.solution)
greedy.run(sort=False)
self.solution.value = self.solution.calculate_value()
self.value = self.solution.value
def setUp(self):
raw_data = dm.Importer()
raw_data.import_data("./tests/cvrp2.test")
data = dm.DataMapper(raw_data)
self.instance = i.ProblemInstance(data)
self.instance.distance_matrix = [
[0, 6, 3, 1, 7, 11],
[6, 0, 5, 9, 6, 3],
[3, 5, 0, 8, 2, 4],
[1, 9, 8, 0, 9, 9],
[7, 6, 2, 9, 0, 3],
[11,3, 4, 9, 3, 0]
]
self.bounded_master = [
[float("inf"), 1., 1., 2., 3., 4., 5., 6.],
[1., float("inf"), float("inf"), 5., 2., 0., 6., 10.],
[1., float("inf"), float("inf"), 5., 2., 0., 6., 10.],
[2., 3., 3., float("inf"), 2., 6., 3., 0.],
[3., 1., 1., 3., float("inf"), 6., 3., 0., 2.],
[4., 0., 0., 8., 7., float("inf"), 8., 8.],
[5., 5., 5., 4., 0., 7., float("inf"), 1.],
[6., 8., 8., 0., 1., 6., 0., float("inf")]
]
def setUp(self):
raw_data = dm.Importer()
raw_data.import_data("./tests/E-n23-k3.vrp")
data = dm.DataMapper(raw_data)
problem = i.ProblemInstance(data)
self.solution = a.Solution(problem)
def setUp(self):
raw_data = dm.Importer()
# raw_data.import_data("./tests/cvrp2.test")
# raw_data.import_data("./tests/ulysses-n16-k3.vrp")
# raw_data.import_data("./tests/E-n23-k3.vrp")
# raw_data.import_data("./tests/cvrp3.test")
# raw_data.import_data("./tests/P-n19-k2.vrp")
raw_data.import_data("./tests/E-n101-k14.vrp")
data = dm.DataMapper(raw_data)
self.instance = i.ProblemInstance(data)
self.solution = a.Solution(self.instance)
greedy = gf.GreedyFirst(self.solution.solution)
greedy.run(sort=False)
self.solution.value = self.solution.eval()
self.tabu_search = tabu.TabuSearch(self.solution, 100)
def setUp(self):
self.test_filelines = [
"NAME : test-E-n6-k4",
"COMMENT : (##This is bullshit##Christophides and Eilon, Min no of trucks: 4, Optimal value: 375)",
"TYPE : CVRP",
"DIMENSION : 6",
"EDGE_WEIGHT_TYPE : EUC_2D",
"CAPACITY : 2500",
"NODE_COORD_SECTION",
"1 145 215",
"2 151 264",
"3 159 261",
"4 130 254",
"5 128 252",
"6 163 247",
"DEMAND_SECTION",
"1 0",
"2 1100",
"3 700",
"4 800",
"5 1400",
"6 2100",
"DEPOT_SECTION",
" 1",
" -1",
"EOF"
]
self.test_node_coordinates_list = [
(float(145), float(215)),
(float(151), float(264)),
(float(159), float(261)),
(float(130), float(254)),
(float(128), float(252)),
(float(163), float(247))
]
self.test_demand_list = [0, 1100, 700, 800, 1400, 2100]
self.testobject = dm.Importer()
self.testobject._read_file("./tests/cvrp1.test")
def setUp(self):
raw_data = dm.Importer()
raw_data.import_data("./tests/cvrp1.test")
data = dm.DataMapper(raw_data)
self.instance = i.ProblemInstance(data)
def main():
import argparse
import time
from code import instance as inst
from code import datamapping as dm
from code import greedyfirst as gf
from code import algorithm as a
from code import baseobjects as bo
from code import tabu
from code import branchnbound as bnb
argparser = argparse.ArgumentParser(description='CVRP_Solver')
argparser.add_argument('-ProblemInstance',
action='store',
dest='ProblemInstance',
help='path to the instance you want to solve',
required=True)
arggroup = argparser.add_mutually_exclusive_group(required=True)
arggroup.add_argument('-Tabu',
action='store_true',
help='use tabu search algorithm')
arggroup.add_argument('-BnB',
action='store_true',
help='use branch and bound algorithm')
args = argparser.parse_args()
problem_path = args.ProblemInstance
max_iterations = 100
raw_data = dm.Importer()
raw_data.import_data(problem_path)
data = dm.DataMapper(raw_data)
instance = inst.ProblemInstance(data)
solution = a.Solution(instance)
greedy_heuristic = gf.GreedyFirst(solution.solution)
greedy_heuristic.run(sort=True)
solution.value = solution.eval()
value_from_greedy = solution.value
if args.Tabu:
tabu_search = tabu.TabuSearch(solution, max_iterations)
print("Starting tabu search")
start = time.process_time()
tabu_search.run()
end = time.process_time()
print("time: " + str(end - start))
print("initial value from greedy heuristic was: " +
str(value_from_greedy))
value_from_tabu = tabu_search.instance.value
print(" value after running tabu search: " +
str(value_from_tabu))
print("routes:", end="")
for i, vehicle in enumerate(tabu_search.instance.solution.fleet):
print("\nvehicle " + str(i + 1) + ": ", end="")
for node in vehicle.route:
print(node.id, end=", ")
print("\n\n")
elif args.BnB:
bnb_algo = bnb.BranchNBound()
bnb_algo.initialize(instance, value_from_greedy)
print(
"Starting branch&bound with initial upper_bound from greedy heuristic"
)
start = time.process_time()
upper_bound, routes, edges, times_branched = bnb_algo.run()
end = time.process_time()
print("time: " + str(end - start))
conv_routes = route_from_edges(routes)
print("initial value: " + str(value_from_greedy))
print("optimal value: " + str(upper_bound))
print("routes:", end="")
for i, route in enumerate(conv_routes):
print("\nvehicle " + str(i + 1) + ": ", end="")
for node in route:
print(node, end=", ")
print("\n\n")
def setUp(self):
self.test_object = dm.Importer()
self.test_object.import_data("./tests/cvrp1.test")
