Small and efficient implementation of the Differential Evolution algorithm using the rand/1/bin schema

differential_evolution.py

import numpy as np

def de(fobj, bounds, mut=0.8, crossp=0.7, popsize=20, its=1000):
    dimensions = len(bounds)
    pop = np.random.rand(popsize, dimensions)
    min_b, max_b = np.asarray(bounds).T
    diff = np.fabs(min_b - max_b)
    pop_denorm = min_b + pop * diff
    fitness = np.asarray([fobj(ind) for ind in pop_denorm])
    best_idx = np.argmin(fitness)
    best = pop_denorm[best_idx]
    for i in range(its):
        for j in range(popsize):
            idxs = [idx for idx in range(popsize) if idx != j]
            a, b, c = pop[np.random.choice(idxs, 3, replace = False)]
            mutant = np.clip(a + mut * (b - c), 0, 1)
            cross_points = np.random.rand(dimensions) < crossp
            if not np.any(cross_points):
                cross_points[np.random.randint(0, dimensions)] = True
            trial = np.where(cross_points, mutant, pop[j])
            trial_denorm = min_b + trial * diff
            f = fobj(trial_denorm)
            if f < fitness[j]:
                fitness[j] = f
                pop[j] = trial
                if f < fitness[best_idx]:
                    best_idx = j
                    best = trial_denorm
        yield best, fitness[best_idx]

Hi,

You have to provide an objective function to optimize, which returns a number. x ** 2 / len(x) in you case is a 32 vector, but sum(x**2)/len(x) is a number.

Cheers,
P

Hi Pablo

Thank you for your response. So you mean if any objective function = f(x) returns a vector/matrix/array will not work. Is it right? In this case, I have to select which dimension of a vector/matric/array such as f [i, j, k] to return?

How about the issue "ImportError: cannot import name 'problem'"? What's wrong?

Thanks

Viet

Yes you are right, you need to assign values to your vectors that you can compare. If your goal is to maximize or minimize other kind of funcion, you would need multiobjective optimization.

The import problems you are having I guess is for not using Yabox?:

pip install yabox

Then in python:

from yabox import problems

It should work.

Cheers

hi Pablo, how I fit the follow function in your code? fobj = lambda x: sum(((1-x) ^2)+ 100*(((x+1) - x^2)^2)/len(x-1)
all the bounds i put give me a SyntaxError: invalid syntax

Python does not use the ^ operator, but ** instead: (1-x)**2 + 100...

Hi Pablo, I have the same problem: cannot import name 'problem' from 'yabox.problems'

I installed yabox in my machine and doesn't work.

Hi how should I change the code to get best/1/bin