#!/usr/bin/env python
# ------------------------------------------------------------------------------------------------------%
# Created by "<NAME>" at 10:11, 16/03/2020                                                        %
#                                                                                                       %
#       Email:      <EMAIL>                                                           %
#       Homepage:   https://www.researchgate.net/profile/Thieu_Nguyen6                                  %
#       Github:     https://github.com/thieu1995                                                  %
#-------------------------------------------------------------------------------------------------------%

from opfunu.cec_basic.cec2014_nobias import *
from mealpy.evolutionary_based.GA import BaseGA


## Setting parameters
obj_func = F5
verbose = False
epoch = 10
pop_size = 50

lb1 = [-3, -5, 1, -10]
ub1 = [5, 10, 100, 30]

md1 = BaseGA(obj_func, lb1, ub1, verbose, epoch, pop_size)
best_pos1, best_fit1, list_loss1 = md1.train()
print(md1.solution[1])



#!/usr/bin/env python
# ------------------------------------------------------------------------------------------------------%
# Created by "<NAME>" at 10:11, 16/03/2020                                                        %
#                                                                                                       %
#       Email:      <EMAIL>                                                           %
#       Homepage:   https://www.researchgate.net/profile/Thieu_Nguyen6                                  %
#       Github:     https://github.com/thieu1995                                                  %
#-------------------------------------------------------------------------------------------------------%

from opfunu.cec_basic.cec2014_nobias import *
from mealpy.evolutionary_based.GA import BaseGA


## Setting parameters
obj_func = F5
verbose = False
epoch = 10
pop_size = 50

lb1 = [-3, -5, 1, -10]
ub1 = [5, 10, 100, 30]

md1 = BaseGA(obj_func, lb1, ub1, verbose, epoch, pop_size)
best_pos1, best_fit1, list_loss1 = md1.train()
print(md1.solution[1])



#!/usr/bin/env python # ------------------------------------------------------------------------------------------------------% # Created by "<NAME>" at 10:11, 16/03/2020                                                        % #                                                                                                       % #       Email:      <EMAIL>                                                           % #       Homepage:   https://www.researchgate.net/profile/Thieu_Nguyen6                                  % #       Github:     https://github.com/thieu1995                                                  % #-------------------------------------------------------------------------------------------------------% ## Setting parameters