#!/usr/bin/env python3
import math
import time
# from tabu import tabu_search
import tabu
# import matplotlib.pyplot as plt
import sys
from os.path import join, dirname
# import CVRPFileParser
sys.path.append(join(dirname(__file__), "../benchmark"))
from cvrp_parser import CVRPFileParser
if __name__ == '__main__':
p = CVRPFileParser('../benchmark/instances/Vrp-Set-A/A-n32-k5.vrp')
# p = CVRPFileParser('../benchmark/instances/Vrp-Set-A/A-n38-k5.vrp')
p.parse()
capacity = p.capacity
distances = p.distances
demands = p.demands
coordinates = p.coordinates
print(capacity)
print(distances)
print(demands)
tabu.MAX_ITER = 2000
time_begin = time.process_time()
costs = []
solution, distance = tabu.tabu_search(capacity=capacity,
distances=distances,
result = dict()
result['iteration'] = args.iter
result['algorithm'] = args.algo
# each instance, we make 5 runs
num_runs = args.num_sample
# case selection of which algo
if args.algo == "tabu_search":
# Tabu search
import tabu_search.tabu as tabu
tabu.MAX_ITER = args.iter
for inst_ in benchmark_instances:
p = CVRPFileParser(inst_)
p.parse()
inst_result = dict()
inst_result['cost'] = []
inst_result['proc_time'] = []
inst_result['sol'] = []
inst_result['loads'] = []
for _ in range(num_runs):
stime = time.process_time()
solution, cost = tabu.tabu_search(
capacity=p.capacity, distances=p.distances, demands=p.demands)
etime = time.process_time()
# save down the cost and cpu time
from cvrp_parser import CVRPFileParser
if __name__ == '__main__':
parser = CVRPFileParser('instances/Vrp-Set-A/A-n32-k5.vrp')
parser.parse()
print(parser.data)
print(parser.capacity)
print(parser.distances)
print(parser.demands)
import GA_VRP
import time
import matplotlib.pyplot as plt
import math
import sys
from os.path import join, dirname
# import CVRPFileParser
sys.path.append(join(dirname(__file__), "../benchmark"))
from cvrp_parser import CVRPFileParser
if __name__ == '__main__':
# p = CVRPFileParser('../benchmark/instances/Vrp-Set-A/A-n32-k5.vrp')
p = CVRPFileParser('../benchmark/instances/Vrp-Set-B/B-n34-k5.vrp')
p.parse()
# ============================
# PUT PARAMETER INTO MODULE
# ============================
GA_VRP.mod_param_config(city_num=p.dimension,
coordinates=p.coordinates,
capacity=p.capacity,
distances=p.distances,
demands=p.demands)
#GA
time_begin = time.process_time()
population = GA_VRP.initialization()
population = GA_VRP.main_GA(population)
best_chromo = population[0]
best_trips = best_chromo.trips