A New Hybrid BA_ABC Algorithm for Global Optimization Problems
Bat Algorithm (BA) and Artificial Bee Colony Algorithm (ABC) are frequently used in solving global optimization problems. Many new algorithms in the literature are obtained by modifying these algorithms for both constrained and unconstrained optimization problems or using them in a hybrid manner wit...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/10/1749 |
| _version_ | 1797551287290560512 |
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| author | Gülnur Yildizdan Ömer Kaan Baykan |
| author_facet | Gülnur Yildizdan Ömer Kaan Baykan |
| author_sort | Gülnur Yildizdan |
| collection | DOAJ |
| description | Bat Algorithm (BA) and Artificial Bee Colony Algorithm (ABC) are frequently used in solving global optimization problems. Many new algorithms in the literature are obtained by modifying these algorithms for both constrained and unconstrained optimization problems or using them in a hybrid manner with different algorithms. Although successful algorithms have been proposed, BA’s performance declines in complex and large-scale problems are still an ongoing problem. The inadequate global search capability of the BA resulting from its algorithm structure is the major cause of this problem. In this study, firstly, inertia weight was added to the speed formula to improve the search capability of the BA. Then, a new algorithm that operates in a hybrid manner with the ABC algorithm, whose diversity and global search capability is stronger than the BA, was proposed. The performance of the proposed algorithm (BA_ABC) was examined in four different test groups, including classic benchmark functions, CEC2005 small-scale test functions, CEC2010 large-scale test functions, and classical engineering design problems. The BA_ABC results were compared with different algorithms in the literature and current versions of the BA for each test group. The results were interpreted with the help of statistical tests. Furthermore, the contribution of BA and ABC algorithms, which constitute the hybrid algorithm, to the solutions is examined. The proposed algorithm has been found to produce successful and acceptable results. |
| first_indexed | 2024-03-10T15:42:25Z |
| format | Article |
| id | doaj.art-7310496b702347fe93037bb6fbacf46b |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T15:42:25Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-7310496b702347fe93037bb6fbacf46b2023-11-20T16:43:19ZengMDPI AGMathematics2227-73902020-10-01810174910.3390/math8101749A New Hybrid BA_ABC Algorithm for Global Optimization ProblemsGülnur Yildizdan0Ömer Kaan Baykan1Kulu Vocational School, Selcuk University, Kulu, 42770 Konya, TurkeyDepartment of Computer Engineering, Faculty of Engineering and Natural Sciences, Konya Technical University, 42250 Konya, TurkeyBat Algorithm (BA) and Artificial Bee Colony Algorithm (ABC) are frequently used in solving global optimization problems. Many new algorithms in the literature are obtained by modifying these algorithms for both constrained and unconstrained optimization problems or using them in a hybrid manner with different algorithms. Although successful algorithms have been proposed, BA’s performance declines in complex and large-scale problems are still an ongoing problem. The inadequate global search capability of the BA resulting from its algorithm structure is the major cause of this problem. In this study, firstly, inertia weight was added to the speed formula to improve the search capability of the BA. Then, a new algorithm that operates in a hybrid manner with the ABC algorithm, whose diversity and global search capability is stronger than the BA, was proposed. The performance of the proposed algorithm (BA_ABC) was examined in four different test groups, including classic benchmark functions, CEC2005 small-scale test functions, CEC2010 large-scale test functions, and classical engineering design problems. The BA_ABC results were compared with different algorithms in the literature and current versions of the BA for each test group. The results were interpreted with the help of statistical tests. Furthermore, the contribution of BA and ABC algorithms, which constitute the hybrid algorithm, to the solutions is examined. The proposed algorithm has been found to produce successful and acceptable results.https://www.mdpi.com/2227-7390/8/10/1749artificial bee colony algorithmbat algorithmcontinuous optimizationheuristic algorithmslarge-scale optimization |
| spellingShingle | Gülnur Yildizdan Ömer Kaan Baykan A New Hybrid BA_ABC Algorithm for Global Optimization Problems Mathematics artificial bee colony algorithm bat algorithm continuous optimization heuristic algorithms large-scale optimization |
| title | A New Hybrid BA_ABC Algorithm for Global Optimization Problems |
| title_full | A New Hybrid BA_ABC Algorithm for Global Optimization Problems |
| title_fullStr | A New Hybrid BA_ABC Algorithm for Global Optimization Problems |
| title_full_unstemmed | A New Hybrid BA_ABC Algorithm for Global Optimization Problems |
| title_short | A New Hybrid BA_ABC Algorithm for Global Optimization Problems |
| title_sort | new hybrid ba abc algorithm for global optimization problems |
| topic | artificial bee colony algorithm bat algorithm continuous optimization heuristic algorithms large-scale optimization |
| url | https://www.mdpi.com/2227-7390/8/10/1749 |
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