@@ -845,7 +845,7 @@ Release Date: 28 September 2021
845845 ``save_solutions=True ``.
846846
8478472. The user can use the ``tqdm `` library to show a progress bar.
848- https://github.com/ahmedfgad/GeneticAlgorithmPython/discussions/50
848+ https://github.com/ahmedfgad/GeneticAlgorithmPython/discussions/50.
849849
850850..code ::python
851851
@@ -874,6 +874,50 @@ Release Date: 28 September 2021
874874
875875 ga_instance.plot_result()
876876
877+ ga_instance `` will be pickled (i.e.
878+ the ``save() `` method will be called.
879+
880+ ..code ::python
881+
882+ ga_instance.save(" test"
883+
884+
885+ ``on_generation `` parameter. In the next code, the
886+ ``on_generation_progress() `` function is defined which updates the
887+ progress bar.
888+
889+ ..code ::python
890+
891+ import pygad
892+ import numpy
893+ import tqdm
894+
895+ equation_inputs= [4 ,- 2 ,3.5 ]
896+ desired_output= 44
897+
898+ def fitness_func (solution ,solution_idx ):
899+ output= numpy.sum(solution* equation_inputs)
900+ fitness= 1.0 / (numpy.abs(output- desired_output)+ 0.000001 )
901+ return fitness
902+
903+ def on_generation_progress (ga ):
904+ pbar.update(1 )
905+
906+ num_generations= 100
907+ with tqdm.tqdm(total = num_generations)as pbar:
908+ ga_instance= pygad.GA(num_generations = num_generations,
909+ sol_per_pop = 5 ,
910+ num_parents_mating = 2 ,
911+ num_genes = len (equation_inputs),
912+ fitness_func = fitness_func,
913+ on_generation = on_generation_progress)
914+
915+ ga_instance.run()
916+
917+ ga_instance.plot_result()
918+
919+ ga_instance.save(" test"
920+
877921solutions `` and
878922 ``solutions_fitness `` when the ``save_solutions `` parameter is set to
879923 ``True ``. Now, the fitness of the last population is appended to the
@@ -1366,8 +1410,8 @@ A number of research papers used PyGAD and here are some of them:
13661410- Jaros, Marta, and Jiri Jaros. "Performance-Cost Optimization of
13671411 Moldable Scientific Workflows."
13681412
1369- - Thorat, Divya.* Enhanced genetic algorithm to reduce makespan of
1370- multiple jobs in map-reduce application on serverless platform * .
1413+ - Thorat, Divya." Enhanced genetic algorithm to reduce makespan of
1414+ multiple jobs in map-reduce application on serverless platform" .
13711415 Diss. Dublin, National College of Ireland, 2020.
13721416
13731417- Koch, Chris, and Edgar Dobriban. "AttenGen: Generating Live
@@ -1389,6 +1433,19 @@ A number of research papers used PyGAD and here are some of them:
13891433 Long Short-Term Memory Network for Long-Term Load Forecasting." *IEEE
13901434 Access * 9 (2021): 68511-68522.
13911435
1436+ - Antunes, E. D. O., Caetano, M. F., Marotta, M. A., Araujo, A.,
1437+ Bondan, L., Meneguette, R. I., & Rocha Filho, G. P. (2021, August).
1438+ Soluções Otimizadas para o Problema de Localização de Máxima
1439+ Cobertura em Redes Militarizadas 4G/LTE. In *Anais do XXVI Workshop
1440+ de Gerência e Operação de Redes e Serviços * (pp. 152-165). SBC.
1441+
1442+ More Links
1443+ ==========
1444+
1445+ https://rodriguezanton.com/identifying-contact-states-for-2d-objects-using-pygad-and/
1446+
1447+ https://torvaney.github.io/projects/t9-optimised
1448+
13921449For More Information
13931450====================
13941451