A Novel Essential Mutation Method for Evolutionary Algorithms

The mutation is one of the operators that is used by many Evolutionary Algorithms (EA) to diversify the population (solutions). It can enhance the algorithm exploration of the problem search space and improve the evolution process. This paper introduces a novel mutation technique that is based on a...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abou Doush, Iyad (author)
منشور في: 2022
الوصول للمادة أونلاين:https://dspace.auk.edu.kw/handle/11675/9626
https://ieeexplore.ieee.org/document/9873805
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author Abou Doush, Iyad
author_facet Abou Doush, Iyad
author_role author
dc.contributor.none.fl_str_mv Al-Betar, Mohammed Azmi
Awadallah, Mohammed
dc.creator.none.fl_str_mv Abou Doush, Iyad
dc.date.none.fl_str_mv 2022-07-11
2023-04-09T10:32:28Z
2023-04-09T10:32:28Z
dc.identifier.none.fl_str_mv I. A. Doush, M. A. Awadallah and M. A. Al-Betar, A Novel Essential Mutation Method for Evolutionary Algorithms, 2022 2nd International Conference on Computing and Machine Intelligence (ICMI), 2022, pp. 1-5, doi: 10.1109/ICMI55296.2022.9873805.
https://dspace.auk.edu.kw/handle/11675/9626
https://ieeexplore.ieee.org/document/9873805
dc.publisher.none.fl_str_mv 2nd International Conference on Computing and Machine Intelligence ICMI-2022
dc.relation.none.fl_str_mv College of Engineering & Applied Sciences
dc.title.none.fl_str_mv A Novel Essential Mutation Method for Evolutionary Algorithms
dc.type.none.fl_str_mv Conference Presentations/Proceedings
info:eu-repo/semantics/publishedVersion
description The mutation is one of the operators that is used by many Evolutionary Algorithms (EA) to diversify the population (solutions). It can enhance the algorithm exploration of the problem search space and improve the evolution process. This paper introduces a novel mutation technique that is based on a recently investigated mutation bias pattern in the Arabidopsis thaliana plant [1]. The proposed mutation technique is called an essential mutation. The proposed method uses the ϵ parameter to control the amount of distance we can be from the parent's fitness. Three different configurations are studied and the best results are obtained when ϵ=0. It is compared against five well-known mutation techniques which are Boundary, Non-uniform, MPT, and Polynomial on standard benchmark functions. The obtained results show the superiority of the proposed essential mutation in terms of best solution and convergence speed in most of the test functions.
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identifier_str_mv I. A. Doush, M. A. Awadallah and M. A. Al-Betar, A Novel Essential Mutation Method for Evolutionary Algorithms, 2022 2nd International Conference on Computing and Machine Intelligence (ICMI), 2022, pp. 1-5, doi: 10.1109/ICMI55296.2022.9873805.
network_acronym_str AUKR
network_name_str AU Kuwait Rep
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publishDate 2022
publisher.none.fl_str_mv 2nd International Conference on Computing and Machine Intelligence ICMI-2022
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spelling A Novel Essential Mutation Method for Evolutionary AlgorithmsAbou Doush, IyadThe mutation is one of the operators that is used by many Evolutionary Algorithms (EA) to diversify the population (solutions). It can enhance the algorithm exploration of the problem search space and improve the evolution process. This paper introduces a novel mutation technique that is based on a recently investigated mutation bias pattern in the Arabidopsis thaliana plant [1]. The proposed mutation technique is called an essential mutation. The proposed method uses the ϵ parameter to control the amount of distance we can be from the parent's fitness. Three different configurations are studied and the best results are obtained when ϵ=0. It is compared against five well-known mutation techniques which are Boundary, Non-uniform, MPT, and Polynomial on standard benchmark functions. The obtained results show the superiority of the proposed essential mutation in terms of best solution and convergence speed in most of the test functions.2nd International Conference on Computing and Machine Intelligence ICMI-2022Al-Betar, Mohammed Azmi Awadallah, Mohammed2023-04-09T10:32:28Z2023-04-09T10:32:28Z2022-07-11Conference Presentations/Proceedingsinfo:eu-repo/semantics/publishedVersionI. A. Doush, M. A. Awadallah and M. A. Al-Betar, A Novel Essential Mutation Method for Evolutionary Algorithms, 2022 2nd International Conference on Computing and Machine Intelligence (ICMI), 2022, pp. 1-5, doi: 10.1109/ICMI55296.2022.9873805.https://dspace.auk.edu.kw/handle/11675/9626https://ieeexplore.ieee.org/document/9873805College of Engineering & Applied Sciencesoai:dspace.auk.edu.kw:11675/96262024-04-07T11:36:18Z
spellingShingle A Novel Essential Mutation Method for Evolutionary Algorithms
Abou Doush, Iyad
status_str publishedVersion
title A Novel Essential Mutation Method for Evolutionary Algorithms
title_full A Novel Essential Mutation Method for Evolutionary Algorithms
title_fullStr A Novel Essential Mutation Method for Evolutionary Algorithms
title_full_unstemmed A Novel Essential Mutation Method for Evolutionary Algorithms
title_short A Novel Essential Mutation Method for Evolutionary Algorithms
title_sort A Novel Essential Mutation Method for Evolutionary Algorithms
url https://dspace.auk.edu.kw/handle/11675/9626
https://ieeexplore.ieee.org/document/9873805