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base_metaheuristic.py
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base_metaheuristic.py
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#!python3
# Copyright (C) 2020 Victor O. Costa
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
from abc import ABC, abstractmethod
class Base:
""" """
def __init__(self):
""" Constructor """
self.verbosity = True
# Initial (NULL) problem definition
self.num_variables = None # Number of variables
self.initial_ranges = [] # Initialization boundaries for each variable
self.is_bounded = [] # Here, if a variable is constrained, it will be limited to its initialization boundaries for all the search
self.cost_function = None # Cost function to guide the search
def set_verbosity(self, status):
""" If verbosity is set True, print partial results of the search will be printed """
# Input error checking
if not (type(status) is bool):
print("Error, verbosity parameter must be a boolean")
exit(-1)
self.verbosity = status
def set_cost(self, cost_function):
""" Sets the cost function that will guide the search """
self.cost_function = cost_function
@abstractmethod
def define_variables(self, initial_ranges, is_bounded):
pass
@abstractmethod
def optimize(self):
pass