Collaborative Libraries

In this section, we will guide you how to integrate our library into other Optimization frameworks.

Mealpy Library

For example:

from opfunu.cec_based import cec2017
f3 = cec2017.F32017(ndim=30)

from mealpy import GA, FloatVar

problem = {
    "obj_func": f3.evaluate,
    "bounds": FloatVar(lb=f3.lb, ub=f3.ub),
    "minmax": "min",
}
model = GA.BaseGA(epoch=100, pop_size=50)
gbest = model.solve(problem_dict1)
print(f"Solution: {gbest.solution}, Fit: {gbest.target.fitness}")

ScikitOpt Library

For example:

from opfunu.cec_based import cec2015
f10 = cec2015.F102015(ndim=30)

from sko.DE import DE

de = DE(func=f10.evaluate, lb=f10.lb, ub=f10.ub,
                                size_pop=50, max_iter=800)
best_x, best_y = de.run()
print(f"best_x: {best_x}, best_y: {best_y}")

Opytimizer Library

For example:

from opfunu.cec_based import cec2022
f5 = cec2022.F52022(ndim=30)

from opytimizer import Opytimizer
from opytimizer.core import Function
from opytimizer.optimizers.swarm import PSO
from opytimizer.spaces import SearchSpace

space = SearchSpace(n_agents=20, n_variables=f5.ndim,
                lower_bound=f5.lb, upper_bound=f5.ub)
optimizer = PSO()
function = Function(f5.evaluate)

opt = Opytimizer(space, optimizer, function)
opt.start(n_iterations=1000)