Genetic algorithm parenting fitness

dc.citation.epage574
dc.citation.issue2
dc.citation.journalTitleМатематичне моделювання та комп'ютинг
dc.citation.spage566
dc.contributor.affiliationУніверситет Хасана ІІ Касабланки
dc.contributor.affiliationHassan II of Casablanca University
dc.contributor.authorУіс, М.
dc.contributor.authorЕттауфік, А.
dc.contributor.authorМарзак, А.
dc.contributor.authorТрага, А.
dc.contributor.authorOuiss, M.
dc.contributor.authorEttaoufik, A.
dc.contributor.authorMarzak, A.
dc.contributor.authorTragha, A.
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-03-04T10:28:13Z
dc.date.created2023-02-28
dc.date.issued2023-02-28
dc.description.abstractФазова схема еволюції, в якій генетичні алгоритми відбирають особин, що сформують нову популяцію, мала важливий вплив на ці алгоритми. У літературі існує багато підходів. Однак ці підходи враховують лише значення функції відповідності, щоб відрізнити найкращі рішення від гірших. Ця стаття знайомить із придатністю для батьківства, новим параметром, який визначає здатність індивіда народжувати найпридатніших нащадків. Поєднання стандартної фітнес–функції та батьківської придатності допомагає генетичному алгоритму бути ефективнішим і, отже, досягати найкращих результатів.
dc.description.abstractThe evolution scheme phase, in which the genetic algorithms select individuals that will form the new population, had an important impact on these algorithms. Many approaches exist in the literature. However, these approaches consider only the value of the fitness function to differenciate best solutions from the worst ones. This article introduces the parenting fitness, a novel parameter, that defines the capacity of an individual to produce fittest offsprings. Combining the standard fitness function and the parenting fitness helps the genetic algorithm to be more efficient, hence, producing best results.
dc.format.extent566-574
dc.format.pages9
dc.identifier.citationGenetic algorithm parenting fitness / M. Ouiss, A. Ettaoufik, A. Marzak, A. Tragha // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 10. — No 2. — P. 566–574.
dc.identifier.citationenGenetic algorithm parenting fitness / M. Ouiss, A. Ettaoufik, A. Marzak, A. Tragha // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 10. — No 2. — P. 566–574.
dc.identifier.doidoi.org/10.23939/mmc2023.02.566
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/63418
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofМатематичне моделювання та комп'ютинг, 2 (10), 2023
dc.relation.ispartofMathematical Modeling and Computing, 2 (10), 2023
dc.relation.references[1] Holland J. H. Adaptation in Natural and Artificial Systems. University of Michigan Press (1975).
dc.relation.references[2] Vose M. D. The Simple Genetic Algorithm: Foundations and Theory. Complex Adaptive Systems. MIT Press (1999).
dc.relation.references[3] Goldberg D. E. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Inc. (1989).
dc.relation.references[4] Kenneth E., Kinnear Jr. Advances in Genetic Programming. MIT Press (1994).
dc.relation.references[5] Goldberg D. E., Kalyanmoy D. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms. Foundations of Genetic Algorithms. 1, 69–93 (1991).
dc.relation.references[6] Moscato P. On genetic crossover operators for relative order preservation. C3P Report (1989).
dc.relation.references[7] Syswerda G. Uniform Crossover in Genetic Algorithms. Proceedings of the 3rd International Conference on Genetic Algorithms. 2–9 (1989).
dc.relation.references[8] Saini N. Review of Selection Methods in Genetic Algorithms. International Journal of Engineering and Computer Science. 6 (12), 22261–22263 (2017).
dc.relation.references[9] Dianati M., Song I., Treiber M. An Introduction to Genetic Algorithms and Evolution Strategies (2002).
dc.relation.references[10] McCall J. Genetic algorithms for modelling and optimisation. Journal of Computational and Applied Mathematics. 184 (1), 205–222 (2005).
dc.relation.references[11] De J K. A. An Analysis of the Behavior of a Class of Genetic Adaptive Systems (1975).
dc.relation.references[12] Dantzig G. B., Ramser J. H. The Truck Dispatching Problem. Management Science. 6 (1), 80–91 (1959).
dc.relation.references[13] Laporte G. The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research. 59 (3), 345–358 (1992).
dc.relation.references[14] Sacramento D. Vehicle Routing Problem with Drones Instances. https://zenodo.org/record/1403150.
dc.relation.references[15] Murray C. C., Chu A. G. The Flying Sidekick Traveling Salesman Problem: Optimization of Drone-assisted Parcel Delivery. Transportation Research Part C: Emerging Technologies. 54, 86–109 (2015).
dc.relation.referencesen[1] Holland J. H. Adaptation in Natural and Artificial Systems. University of Michigan Press (1975).
dc.relation.referencesen[2] Vose M. D. The Simple Genetic Algorithm: Foundations and Theory. Complex Adaptive Systems. MIT Press (1999).
dc.relation.referencesen[3] Goldberg D. E. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Inc. (1989).
dc.relation.referencesen[4] Kenneth E., Kinnear Jr. Advances in Genetic Programming. MIT Press (1994).
dc.relation.referencesen[5] Goldberg D. E., Kalyanmoy D. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms. Foundations of Genetic Algorithms. 1, 69–93 (1991).
dc.relation.referencesen[6] Moscato P. On genetic crossover operators for relative order preservation. P.3P Report (1989).
dc.relation.referencesen[7] Syswerda G. Uniform Crossover in Genetic Algorithms. Proceedings of the 3rd International Conference on Genetic Algorithms. 2–9 (1989).
dc.relation.referencesen[8] Saini N. Review of Selection Methods in Genetic Algorithms. International Journal of Engineering and Computer Science. 6 (12), 22261–22263 (2017).
dc.relation.referencesen[9] Dianati M., Song I., Treiber M. An Introduction to Genetic Algorithms and Evolution Strategies (2002).
dc.relation.referencesen[10] McCall J. Genetic algorithms for modelling and optimisation. Journal of Computational and Applied Mathematics. 184 (1), 205–222 (2005).
dc.relation.referencesen[11] De J K. A. An Analysis of the Behavior of a Class of Genetic Adaptive Systems (1975).
dc.relation.referencesen[12] Dantzig G. B., Ramser J. H. The Truck Dispatching Problem. Management Science. 6 (1), 80–91 (1959).
dc.relation.referencesen[13] Laporte G. The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research. 59 (3), 345–358 (1992).
dc.relation.referencesen[14] Sacramento D. Vehicle Routing Problem with Drones Instances. https://zenodo.org/record/1403150.
dc.relation.referencesen[15] Murray C. C., Chu A. G. The Flying Sidekick Traveling Salesman Problem: Optimization of Drone-assisted Parcel Delivery. Transportation Research Part C: Emerging Technologies. 54, 86–109 (2015).
dc.relation.urihttps://zenodo.org/record/1403150
dc.rights.holder© Національний університет “Львівська політехніка”, 2023
dc.subjectgenetic algorithm
dc.subjectfitness function
dc.subjectparenting fitness
dc.subjectoptimization
dc.titleGenetic algorithm parenting fitness
dc.title.alternativeГенетичний алгоритм виховання
dc.typeArticle

Files

Original bundle

Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
2023v10n2_Ouiss_M-Genetic_algorithm_parenting_566-574.pdf
Size:
994.64 KB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
2023v10n2_Ouiss_M-Genetic_algorithm_parenting_566-574__COVER.png
Size:
433.81 KB
Format:
Portable Network Graphics

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.84 KB
Format:
Plain Text
Description: