59 lines
1.7 KiB
Python
Executable File
59 lines
1.7 KiB
Python
Executable File
from preprocessing import parse_file
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from genetic_algorithm import genetic_algorithm
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from memetic_algorithm import memetic_algorithm
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from time import time
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from argparse import ArgumentParser
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def execute_algorithm(args, n, m, data):
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if args.algorithm == "genetic":
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return genetic_algorithm(
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n,
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m,
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data,
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select_mode=args.selection,
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crossover_mode=args.crossover,
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max_iterations=100,
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)
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return memetic_algorithm(
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n,
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m,
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data,
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hybridation=args.hybridation,
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max_iterations=100,
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)
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def show_results(solution, time_delta):
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duplicates = solution.duplicated().any()
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print(solution)
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print(f"Total distance: {solution.fitness.values[0]}")
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if not duplicates:
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print("No duplicates found")
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print(f"Execution time: {time_delta}")
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def parse_arguments():
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parser = ArgumentParser()
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parser.add_argument("file", help="dataset of choice")
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subparsers = parser.add_subparsers(dest="algorithm")
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parser_genetic = subparsers.add_parser("genetic")
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parser_memetic = subparsers.add_parser("memetic")
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parser_genetic.add_argument("crossover", choices=["uniform", "position"])
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parser_genetic.add_argument("selection", choices=["generational", "stationary"])
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parser_memetic.add_argument("hybridation", choices=["all", "random", "best"])
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return parser.parse_args()
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def main():
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args = parse_arguments()
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n, m, data = parse_file(args.file)
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start_time = time()
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solutions = execute_algorithm(args, n, m, data)
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end_time = time()
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show_results(solutions, time_delta=end_time - start_time)
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if __name__ == "__main__":
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main()
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