An adaptive gravitational search algorithm for global optimization
Optimization algorithm has become one of the most studied branches in the fields of artificial intelligent and soft computing. Many powerful optimization algorithms with global search ability can be found in the literature. Gravitational Search Algorithm (GSA) is one of the relatively new population...
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Institute of Advanced Engineering and Science
2023
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my.uniten.dspace-249412023-05-29T15:29:13Z An adaptive gravitational search algorithm for global optimization Koay Y.-Y. Tan J.-D. Lim C.-W. Koh S.-P. Tiong S.-K. Ali K. 57189626122 38863172300 35722335000 22951210700 15128307800 36130958600 Optimization algorithm has become one of the most studied branches in the fields of artificial intelligent and soft computing. Many powerful optimization algorithms with global search ability can be found in the literature. Gravitational Search Algorithm (GSA) is one of the relatively new population-based optimization algorithms. In this research, an Adaptive Gravitational Search Algorithm (AGSA) is proposed. The AGSA is enhanced with an adaptive search step local search mechanism. The adaptive search step begins the search with relatively larger step size, and automatically fine-tunes the step size as iterations go. This enhancement grants the algorithm a more powerful exploitation ability, which in turn grants solutions with higher accuracies. The proposed AGSA was tested in a test suit with several well-established optimization test functions. The results showed that the proposed AGSA out-performed other algorithms such as conventional GSA and Genetic Algorithm in the benchmarking of speed and accuracy. It can thus be concluded that the proposed AGSA performs well in solving local and global optimization problems. Applications of the AGSA to solve practical engineering optimization problems can be considered in the future. Copyright � 2019 Institute of Advanced Engineering and Science. All rights reserved. Final 2023-05-29T07:29:13Z 2023-05-29T07:29:13Z 2019 Article 10.11591/ijeecs.v16.i2.pp724-729 2-s2.0-85073562079 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073562079&doi=10.11591%2fijeecs.v16.i2.pp724-729&partnerID=40&md5=6fcd801280feab4ec889a8db61b2c1c6 https://irepository.uniten.edu.my/handle/123456789/24941 16 2 724 729 All Open Access, Hybrid Gold Institute of Advanced Engineering and Science Scopus |
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Optimization algorithm has become one of the most studied branches in the fields of artificial intelligent and soft computing. Many powerful optimization algorithms with global search ability can be found in the literature. Gravitational Search Algorithm (GSA) is one of the relatively new population-based optimization algorithms. In this research, an Adaptive Gravitational Search Algorithm (AGSA) is proposed. The AGSA is enhanced with an adaptive search step local search mechanism. The adaptive search step begins the search with relatively larger step size, and automatically fine-tunes the step size as iterations go. This enhancement grants the algorithm a more powerful exploitation ability, which in turn grants solutions with higher accuracies. The proposed AGSA was tested in a test suit with several well-established optimization test functions. The results showed that the proposed AGSA out-performed other algorithms such as conventional GSA and Genetic Algorithm in the benchmarking of speed and accuracy. It can thus be concluded that the proposed AGSA performs well in solving local and global optimization problems. Applications of the AGSA to solve practical engineering optimization problems can be considered in the future. Copyright � 2019 Institute of Advanced Engineering and Science. All rights reserved. |
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57189626122 |
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57189626122 Koay Y.-Y. Tan J.-D. Lim C.-W. Koh S.-P. Tiong S.-K. Ali K. |
| format |
Article |
| author |
Koay Y.-Y. Tan J.-D. Lim C.-W. Koh S.-P. Tiong S.-K. Ali K. |
| spellingShingle |
Koay Y.-Y. Tan J.-D. Lim C.-W. Koh S.-P. Tiong S.-K. Ali K. An adaptive gravitational search algorithm for global optimization |
| author_sort |
Koay Y.-Y. |
| title |
An adaptive gravitational search algorithm for global optimization |
| title_short |
An adaptive gravitational search algorithm for global optimization |
| title_full |
An adaptive gravitational search algorithm for global optimization |
| title_fullStr |
An adaptive gravitational search algorithm for global optimization |
| title_full_unstemmed |
An adaptive gravitational search algorithm for global optimization |
| title_sort |
adaptive gravitational search algorithm for global optimization |
| publisher |
Institute of Advanced Engineering and Science |
| publishDate |
2023 |
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1806423270536249344 |
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13.211869 |