Comments (2)
That's very helpful! Thank you and sorry for the confusion. I appreciate the response and love the project!
from geneticalgorithmpython.
There is nothing wrong. Just let me explain how things are calculated.
Given that there are N solutions in the population, then internally to PyGAD
the fitness function fitness_func()
will be called N times, once for each solution.
Inside the callback_generation()
function, the first line executed does not make the fitness function to be called at all. So, the number of times fitness_func()
is called is still N.
The second line in callback_generation()
calls the best_solution()
method which in turn calls fitness_func()
. So, for each of the N solutions, fitness_func()
is called twice in the generation, one internally to PyGAD and another by the best_solution()
. So, the total number of calls is 2N.
Note that there is an attribute called last_generation_fitness
which holds the fitness values of the last generation. You can use it rather than calling best_solution()
.
I hope this makes things clear.
from geneticalgorithmpython.
Related Issues (20)
- neural evolution in latent space?
- Variable population size HOT 6
- KerasGA Parellel Processing HOT 1
- Wor HOT 1
- Additive random mutation with `gene_space` `low` and `high` HOT 2
- AttributeError HOT 1
- Adding interactive examples HOT 1
- Multi-Objective Optimization and parallel_processing
- Exceptions when running multi-objective problems HOT 1
- Save the instance of a GA during fitness evaluation HOT 1
- Error when run parallel_processing "process" HOT 3
- multi objective optimization - metric of quality HOT 1
- Force recalculation of fitness values for each new generation ? HOT 7
- Fitness value of a solution computed multiple times per generation? HOT 5
- The on_generation callback is not called at the end of generation 0 HOT 2
- GA
- Convergence issue: good solution appears to be forgotten, resulting best solution is not even valid HOT 1
- Error when running 3.2.0 vs. 3.1.0 for ga_instance.best_solutions
- ga_instance.save will not work with tqdm example HOT 1
- fitness function is being saved? HOT 2
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