Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization
Several metaheuristic algorithms and improvements to the existing ones have been presented over the years. Most of these algorithms were inspired either by nature or the behavior of certain swarms, such as birds, ants, bees, or even bats. These algorithms have two major components, which are explora...
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| Language: | English |
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Springer International Publishing
2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/1/Novel%20Multi-Swarm%20Approach%20for%20Balancing%20Exploration1.pdf |
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ump-222712019-01-24T04:54:26Z http://umpir.ump.edu.my/id/eprint/22271/ Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization Salih, Sinan Q. Alsewari, Abdulrahman A. Al-Khateeb, Bellal Mohamad Fadli, Zolkipli Q Science (General) T Technology (General) Several metaheuristic algorithms and improvements to the existing ones have been presented over the years. Most of these algorithms were inspired either by nature or the behavior of certain swarms, such as birds, ants, bees, or even bats. These algorithms have two major components, which are exploration and exploitation. The interaction of these components can have a significant influence on the efficiency of the metaheuristics. Meanwhile, there are basically no guiding principles on how to strike a balance between these two components. This study, therefore, proposes a new multi-swarm-based balancing mechanism for keeping a balancing between the exploration and exploitation attributes of metaheuristics. The new approach is inspired by the phenomenon of the leadership scenario among a group of people (a group of people being governed by a selected leader(s)). These leaders communicate in a meeting room, and the overall best leader makes the final decision. The simulation aspect of the study considered several benchmark functions and compared the performance of the suggested algorithm to that of the standard PSO (SPSO) in terms of efficiency. Springer International Publishing 2019 Book Section PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22271/1/Novel%20Multi-Swarm%20Approach%20for%20Balancing%20Exploration1.pdf Salih, Sinan Q. and Alsewari, Abdulrahman A. and Al-Khateeb, Bellal and Mohamad Fadli, Zolkipli (2019) Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization. In: Recent Trends in Data Science and Soft Computing. Springer International Publishing, Cham, pp. 196-206. ISBN 978-3-319-99007-1 https://doi.org/10.1007/978-3-319-99007-1_19 https://doi.org/10.1007/978-3-319-99007-1_19 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
| building |
UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
Q Science (General) T Technology (General) |
| spellingShingle |
Q Science (General) T Technology (General) Salih, Sinan Q. Alsewari, Abdulrahman A. Al-Khateeb, Bellal Mohamad Fadli, Zolkipli Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| description |
Several metaheuristic algorithms and improvements to the existing ones have been presented over the years. Most of these algorithms were inspired either by nature or the behavior of certain swarms, such as birds, ants, bees, or even bats. These algorithms have two major components, which are exploration and exploitation. The interaction of these components can have a significant influence on the efficiency of the metaheuristics. Meanwhile, there are basically no guiding principles on how to strike a balance between these two components. This study, therefore, proposes a new multi-swarm-based balancing mechanism for keeping a balancing between the exploration and exploitation attributes of metaheuristics. The new approach is inspired by the phenomenon of the leadership scenario among a group of people (a group of people being governed by a selected leader(s)). These leaders communicate in a meeting room, and the overall best leader makes the final decision. The simulation aspect of the study considered several benchmark functions and compared the performance of the suggested algorithm to that of the standard PSO (SPSO) in terms of efficiency. |
| format |
Book Section |
| author |
Salih, Sinan Q. Alsewari, Abdulrahman A. Al-Khateeb, Bellal Mohamad Fadli, Zolkipli |
| author_facet |
Salih, Sinan Q. Alsewari, Abdulrahman A. Al-Khateeb, Bellal Mohamad Fadli, Zolkipli |
| author_sort |
Salih, Sinan Q. |
| title |
Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| title_short |
Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| title_full |
Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| title_fullStr |
Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| title_full_unstemmed |
Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization |
| title_sort |
novel multi-swarm approach for balancing exploration and exploitation in particle swarm optimization |
| publisher |
Springer International Publishing |
| publishDate |
2019 |
| url |
http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/ http://umpir.ump.edu.my/id/eprint/22271/1/Novel%20Multi-Swarm%20Approach%20for%20Balancing%20Exploration1.pdf |
| first_indexed |
2023-09-18T22:33:04Z |
| last_indexed |
2023-09-18T22:33:04Z |
| _version_ |
1777416414642044928 |