main.py

import sys
import json
from solution import *


def read_instance_json(file_path):
    with open(file_path) as f:
        return json.load(f)


def write_instance_json(solution, file_path):
    with open(file_path, 'w') as f:
        json.dump(solution, f)


def print_our_solution(best_route, best_cost):
    print("Our route:", best_route)
    print("Our cost:", round(best_cost))


def print_best_solution(instance):
    print("Best route:", instance['GlobalBest'])
    print("Best cost:", instance['GlobalBestVal'])


# TODO: instead of calculate_distance create incremental evaluation
# TODO: look into distance calculation. It seems the matrices are inaccurate because they use only int
# TODO: look for better hyperparameters
# TODO: are these methods the best possible ones?

instance_path = sys.argv[1]
output_path = sys.argv[2]

instance = read_instance_json(instance_path)

best_route, best_cost = lns(instance['Matrix'], instance['Coordinates'], instance['Timeout']-1)

# TODO: before submission comment out the next part
print_our_solution(best_route, best_cost)
print_best_solution(instance)

write_instance_json(best_route, output_path)

# naive_solution = [i for i in range(len(instance['Matrix']))]
# write_instance_json(naive_solution, output_path)

#######################################################################
# Example of the required timeout mechanism within the LNS structure: #
#######################################################################
# ...
# time_limit = instance['Timeout']
# start_time = time.time()
# for iteration in range(9999999999):
#     ...logic of one search iteration...
#     if time.time() - start_time >= time_limit:
#         break
# ...
#######################################################################
#######################################################################