How can I run with N-dimensional functions

[AllSundayCroco]

Could you please give an example for running N-dimensional functions such as [sphere dim = 50] with GA optimizer
Thank you so much !!!!!!!!

[thieu1995]

Hi @AllSundayCroco ,
Have you check the file: examples/evolutionary_based/run_test_GA.py

Basically, with sphere function.

from numpy import sum 
from mealpy.evolutionary_based import GA

def sphere(solution):
	return sum(solution**2)

## Setting parameters
epoch = 10                              # Maximum number of generations
pop_size = 50                          # Population size
lb = [-3, -5, 1, -10, ...]		# Enter your lower bound (50 dimensions)
ub = [5, 10, 100, 30, ...]		# Enter your upper bound (50 dimensions)
verbose = True                        # Print out the training process

model = GA.BaseGA(sphere, lb, ub, verbose, epoch, pop_size)		# Create model object 
best_position, best_fitness, list_loss = model.train()			        # Call train() function from object 
# List loss is the best fitness found in each iterations.

Depend on the algorithm you choose, some algorithms have several variant versions, such as PSO.

You can call the class to create a object like above:

model1 = PSO.BasePSO()
model2 = PSO.HPSO_TVAC()

Check the end of the readme.md file to see the variant versions of each algorithm.