Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor
Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. Previous research has shown that Bat Algorithm could provide a good exploration and exploitation of a solution. However, Bat Algorithm can be get trapped in a local minimum in some multi-...
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King Saud bin Abdulaziz University
2019
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my.utem.eprints.244512023-06-12T11:38:29Z http://eprints.utem.edu.my/id/eprint/24451/ Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor Ramli, Mohamad Raziff Abal Abas, Zuraida Desa, Mohammad Ishak Zainal Abidin, Zaheera Al Azzam, Malik Bader Hasan Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. Previous research has shown that Bat Algorithm could provide a good exploration and exploitation of a solution. However, Bat Algorithm can be get trapped in a local minimum in some multi-dimensional functions. Thus, the phenomenon of slow convergence rate and low accuracy still exits. This paper aims to modify the exploitation of Bat Algorithm in optimising the solution by modifying dimensional size and providing inertia weight. Benchmark test function is then performed for the basic Bat Algorithm and the modified Bat Algorithm (MBA) for comparison. The result is analysed according to the number of iteration needed for a convergence toward the objective. From simulations, it is found that the modified dimension and additional inertia weight factor of Bat Algorithm proves to be more effective than the basic Bat Algorithm in terms of searching for a solution while improving quality of results in all cases or significantly improving convergence speed. King Saud bin Abdulaziz University 2019-10 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24451/2/ENHANCED%20CONVERGENCE%20OF%20BAT%20ALGORITHM%202019.PDF Ramli, Mohamad Raziff and Abal Abas, Zuraida and Desa, Mohammad Ishak and Zainal Abidin, Zaheera and Al Azzam, Malik Bader Hasan (2019) Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor. Journal of King Saud University - Computer and Information Sciences, 31 (4). pp. 452-458. ISSN 1319-1578 https://www.sciencedirect.com/science/article/pii/S1319157817304184?via%3Dihub#! 10.1016/j.jksuci.2018.03.010 |
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Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. Previous research has shown that Bat Algorithm could provide a good exploration and exploitation of a solution. However, Bat Algorithm can be get trapped in a local minimum in some multi-dimensional functions. Thus, the phenomenon of slow convergence rate and low accuracy still exits. This paper aims to modify the exploitation of Bat Algorithm in optimising the solution by modifying dimensional size and providing inertia weight. Benchmark test function is then performed for the basic Bat Algorithm and the modified Bat Algorithm (MBA) for comparison. The result is analysed according to the number of iteration needed for a convergence toward the objective. From simulations, it is found that the modified dimension and additional inertia weight factor of Bat Algorithm proves to be more effective than the basic Bat Algorithm in terms of searching for a solution while improving quality of results in all cases or significantly improving convergence speed. |
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Article |
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Ramli, Mohamad Raziff Abal Abas, Zuraida Desa, Mohammad Ishak Zainal Abidin, Zaheera Al Azzam, Malik Bader Hasan |
spellingShingle |
Ramli, Mohamad Raziff Abal Abas, Zuraida Desa, Mohammad Ishak Zainal Abidin, Zaheera Al Azzam, Malik Bader Hasan Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
author_facet |
Ramli, Mohamad Raziff Abal Abas, Zuraida Desa, Mohammad Ishak Zainal Abidin, Zaheera Al Azzam, Malik Bader Hasan |
author_sort |
Ramli, Mohamad Raziff |
title |
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
title_short |
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
title_full |
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
title_fullStr |
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
title_full_unstemmed |
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor |
title_sort |
enhanced convergence of bat algorithm based on dimensional and inertia weight factor |
publisher |
King Saud bin Abdulaziz University |
publishDate |
2019 |
url |
http://eprints.utem.edu.my/id/eprint/24451/2/ENHANCED%20CONVERGENCE%20OF%20BAT%20ALGORITHM%202019.PDF http://eprints.utem.edu.my/id/eprint/24451/ https://www.sciencedirect.com/science/article/pii/S1319157817304184?via%3Dihub#! |
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