An Efficient Universal Bee Colony Optimization Algorithm
The artificial bee colony algorithm is a global optimization algorithm. The artificial bee colony optimization algorithm is easy to fall into local optimal. We proposed an efficient universal bee colony optimization algorithm (EUBCOA). The algorithm adds the search factor u and the selection strateg...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/340553 |
| _version_ | 1827282507160092672 |
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| author | Xuming Han Yidan Wang Chen Cai Limin Wang* Xiuping Hou Linlin Wang |
| author_facet | Xuming Han Yidan Wang Chen Cai Limin Wang* Xiuping Hou Linlin Wang |
| author_sort | Xuming Han |
| collection | DOAJ |
| description | The artificial bee colony algorithm is a global optimization algorithm. The artificial bee colony optimization algorithm is easy to fall into local optimal. We proposed an efficient universal bee colony optimization algorithm (EUBCOA). The algorithm adds the search factor u and the selection strategy of the onlooker bees based on local optimal solution. In order to realize the controllability of algorithm search ability, the search factor u is introduced to improve the global search range and local search range. In the early stage of the iteration, the search scope is expanded and the convergence rate is increased. In the latter part of the iteration, the algorithm uses the selection strategy to improve the algorithm accuracy and convergence rate. We select ten benchmark functions to testify the performance of the algorithm. Experimental results show that the EUBCOA algorithm effectively improves the convergence speed and convergence accuracy of the ABC algorithm. |
| first_indexed | 2024-04-24T09:20:25Z |
| format | Article |
| id | doaj.art-82d873f44f2a44a1a5590eb2a072074c |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:20:25Z |
| publishDate | 2020-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-82d873f44f2a44a1a5590eb2a072074c2024-04-15T16:05:24ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392020-01-0127132033210.17559/TV-20180516081110An Efficient Universal Bee Colony Optimization AlgorithmXuming Han0Yidan Wang1Chen Cai2Limin Wang*3Xiuping Hou4Linlin Wang5School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, ChinaSchool of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, ChinaSchool of Control and Computer Engineering, North China Electric Power University, Changchun 130012, ChinaSchool of Management Science and Information, Engineering, Jilin University Finance and Economics, Changchun 130117, ChinaSchool of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, ChinaSchool of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, ChinaThe artificial bee colony algorithm is a global optimization algorithm. The artificial bee colony optimization algorithm is easy to fall into local optimal. We proposed an efficient universal bee colony optimization algorithm (EUBCOA). The algorithm adds the search factor u and the selection strategy of the onlooker bees based on local optimal solution. In order to realize the controllability of algorithm search ability, the search factor u is introduced to improve the global search range and local search range. In the early stage of the iteration, the search scope is expanded and the convergence rate is increased. In the latter part of the iteration, the algorithm uses the selection strategy to improve the algorithm accuracy and convergence rate. We select ten benchmark functions to testify the performance of the algorithm. Experimental results show that the EUBCOA algorithm effectively improves the convergence speed and convergence accuracy of the ABC algorithm.https://hrcak.srce.hr/file/340553artificial bee colony algorithmfitnesssearch factoruniversal optimization |
| spellingShingle | Xuming Han Yidan Wang Chen Cai Limin Wang* Xiuping Hou Linlin Wang An Efficient Universal Bee Colony Optimization Algorithm Tehnički Vjesnik artificial bee colony algorithm fitness search factor universal optimization |
| title | An Efficient Universal Bee Colony Optimization Algorithm |
| title_full | An Efficient Universal Bee Colony Optimization Algorithm |
| title_fullStr | An Efficient Universal Bee Colony Optimization Algorithm |
| title_full_unstemmed | An Efficient Universal Bee Colony Optimization Algorithm |
| title_short | An Efficient Universal Bee Colony Optimization Algorithm |
| title_sort | efficient universal bee colony optimization algorithm |
| topic | artificial bee colony algorithm fitness search factor universal optimization |
| url | https://hrcak.srce.hr/file/340553 |
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