Release Date 29 January 20241. Solve bugs when multi-objective optimization is used.#2382. When the `stop_ciiteria` parameter is used with the `reach` keyword, then multiple numeric values can be passed when solving a multi-objective problem. For example, if a problem has 3 objective functions, then `stop_criteria="reach_10_20_30"` means the GA stops if the fitness of the 3 objectives are at least 10, 20, and 30, respectively. The number values must match the number of objective functions. If a single value found (e.g. `stop_criteria=reach_5`) when solving a multi-objective problem, then it is used across all the objectives.#2383. The `delay_after_gen` parameter is now deprecated and will be removed in a future release. If it is necessary to have a time delay after each generation, then assign a callback function/method to the `on_generation` parameter to pause the evolution.4. Parallel processing now supports calculating the fitness during adaptive mutation.#2015. The population size can be changed during runtime by changing all the parameters that would affect the size of any thing used by the GA. For more information, check the [Change Population Size during Runtime](https://pygad.readthedocs.io/en/latest/pygad_more.html#change-population-size-during-runtime) section.#2346. When a dictionary exists in the `gene_space` parameter without a step, then mutation occurs by adding a random value to the gene value. The random vaue is generated based on the 2 parameters `random_mutation_min_val` and `random_mutation_max_val`. For more information, check the [How Mutation Works with the gene_space Parameter?](https://pygad.readthedocs.io/en/latest/pygad_more.html#how-mutation-works-with-the-gene-space-parameter) section.#2297. Add `object` as a supported data type for int (GA.supported_int_types) and float (GA.supported_float_types).#1748. Use the `raise` clause instead of the `sys.exit(-1)` to terminate the execution.#2139. Fix a bug when multi-objective optimization is used with batch fitness calculation (e.g. `fitness_batch_size` set to a non-zero number).10. Fix a bug in the `pygad.py` script when finding the index of the best solution. It does not work properly with multi-objective optimization where `self.best_solutions_fitness` have multiple columns.