1. The `delay_after_gen` parameter is removed from the `pygad.GA` class constructor. As a result, it is no longer an attribute of the `pygad.GA` class instances. To add a delay after each generation, apply it inside the `on_generation` callback. #283
2. In the `single_point_crossover()` method of the `pygad.utils.crossover.Crossover` class, all the random crossover points are returned before the `for` loop. This is by calling the `numpy.random.randint()` function only once before the loop to generate all the K points (where K is the offspring size). This is compared to calling the `numpy.random.randint()` function inside the `for` loop K times, once for each individual offspring.
3. Bug fix in the `examples/example_custom_operators.py` script. #285
4. While making prediction using the `pygad.torchga.predict()` function, no gradients are calculated.
5. The `gene_type` parameter of the `pygad.helper.unique.Unique.unique_int_gene_from_range()` method accepts the type of the current gene only instead of the full gene_type list.
6. Created a new method called `unique_float_gene_from_range()` inside the `pygad.helper.unique.Unique` class to find a unique floating-point number from a range.
7. Fix a bug in the `pygad.helper.unique.Unique.unique_gene_by_space()` method to return the numeric value only instead of a NumPy array.
8. Refactoring the `pygad/helper/unique.py` script to remove duplicate codes and reformatting the docstrings.
9. The plot_pareto_front_curve() method added to the pygad.visualize.plot.Plot class to visualize the Pareto front for multi-objective problems. It only supports 2 objectives. #279
10. Fix a bug converting a nested NumPy array to a nested list. #300
11. The `Matplotlib` library is only imported when a method inside the `pygad/visualize/plot.py` script is used. This is more efficient than using `import matplotlib.pyplot` at the module level as this causes it to be imported when `pygad` is imported even when it is not needed. #292
12. Fix a bug when minus sign (-) is used inside the `stop_criteria` parameter (e.g. `stop_criteria=["saturate_10", "reach_-0.5"]`). #296
13. Make sure `self.best_solutions` is a list of lists inside the `cal_pop_fitness` method. #293
14. Fix a bug where the `cal_pop_fitness()` method was using the `previous_generation_fitness` attribute to return the parents fitness. This instance attribute was not using the fitness of the latest population, instead the fitness of the population before the last one. The issue is solved by updating the `previous_generation_fitness` attribute to the latest population fitness before the GA completes. #291