[BUG] Auglag algorithm from NLOPT library does not evolve the population

[IgSMS]

Describe the bug
I am trying to use auglag and auglag_eq algorithms from the NLOPT library. However, when I run the code the population does not evolve. In fact, I checked if the gradient was being evaluated, but it wasn't. So, the model is running, but it's not evolving.

It is important to note that all the other algorithms available for pygmo are working correctly.

To Reproduce
The code is quite large, so I will summarise here the structure:

class pygmo_run:
prob = pg.problem(my_udp)
nl_algo = pg.nlopt('auglag')
nl_algo.local_optimizer = pg.nlopt('slsqp')
algo = pg.algorithm(uda = nl_algo)
pop = pg.population(prob, size=10, seed = 0)
pop = algo.evolve(pop)

class my_udp:
def fitness:
def get_bounds:
def gradient:

Expected behavior
The population should evolve and search for the minimum.

Environment (please complete the following information):

• OS: Windows 10
• Installation method: conda
• Version: 2.19