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Adapt main module to the requirements

This commit is contained in:
coolneng 2021-06-22 09:14:50 +02:00
parent 6ccc1cb661
commit 89045a04c8
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
2 changed files with 7 additions and 25 deletions
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2
src/local_search.py
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@ -97,7 +97,7 @@ def evaluate_all_solutions(solutions, data, cores=4):
return fitness return fitness
def local_search(n, m, data, number_solutions=10): def multistart_local_search(n, m, data, number_solutions=10):
initial_solutions = generate_initial_solutions(n, m, data, number_solutions) initial_solutions = generate_initial_solutions(n, m, data, number_solutions)
solutions = [] solutions = []
for solution in initial_solutions: for solution in initial_solutions:

30
src/main.py
View File

@ -1,27 +1,14 @@
from preprocessing import parse_file from preprocessing import parse_file
from genetic_algorithm import genetic_algorithm from local_search import multistart_local_search
from memetic_algorithm import memetic_algorithm from simulated_annealing import simulated_annealing
from time import time from time import time
from argparse import ArgumentParser from argparse import ArgumentParser
def execute_algorithm(args, n, m, data): def execute_algorithm(args, n, m, data):
if args.algorithm == "genetic": if args.algorithm == "annealing":
return genetic_algorithm( return simulated_annealing(n, m, data, max_iterations=100)
n, return multistart_local_search(n, m, data)
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): def show_results(solution, time_delta):
@ -36,12 +23,7 @@ def show_results(solution, time_delta):
def parse_arguments(): def parse_arguments():
parser = ArgumentParser() parser = ArgumentParser()
parser.add_argument("file", help="dataset of choice") parser.add_argument("file", help="dataset of choice")
subparsers = parser.add_subparsers(dest="algorithm") parser.add_argument("algorithm", choices=["annealing", "multisearch"])
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() return parser.parse_args()