MH-P2/src/main.py

from preprocessing import parse_file
from genetic_algorithm import genetic_algorithm
from memetic_algorithm import memetic_algorithm
from time import time
from argparse import ArgumentParser


def execute_algorithm(args, n, m, data):
    if args.algorithm == "genetic":
        return genetic_algorithm(
            n,
            m,
            data,
            select_mode=args.selection,
            crossover_mode=args.crossover,
            max_iterations=100,
        )
    return memetic_algorithm(
        n,
        m,
        data,
        hybridation=args.hybridation,
        max_iterations=100,
    )


def show_results(solution, time_delta):
    duplicates = solution.duplicated().any()
    print(solution)
    print(f"Total distance: {solution.fitness.values[0]}")
    if not duplicates:
        print("No duplicates found")
    print(f"Execution time: {time_delta}")


def parse_arguments():
    parser = ArgumentParser()
    parser.add_argument("file", help="dataset of choice")
    subparsers = parser.add_subparsers(dest="algorithm")
    parser_genetic = subparsers.add_parser("genetic")
    parser_memetic = subparsers.add_parser("memetic")
    parser_genetic.add_argument("crossover", choices=["uniform", "position"])
    parser_genetic.add_argument("selection", choices=["generational", "stationary"])
    parser_memetic.add_argument("hybridation", choices=["all", "random", "best"])
    return parser.parse_args()


def main():
    args = parse_arguments()
    n, m, data = parse_file(args.file)
    start_time = time()
    solutions = execute_algorithm(args, n, m, data)
    end_time = time()
    show_results(solutions, time_delta=end_time - start_time)


if __name__ == "__main__":
    main()