A Developed Artificial Bee Colony Algorithm Based on Cloud Model
The Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2227-7390/6/4/61 |
| _version_ | 1818173964447383552 |
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| author | Ye Jin Yuehong Sun Hongjiao Ma |
| author_facet | Ye Jin Yuehong Sun Hongjiao Ma |
| author_sort | Ye Jin |
| collection | DOAJ |
| description | The Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants. |
| first_indexed | 2024-12-11T19:36:52Z |
| format | Article |
| id | doaj.art-006fe6f501744c09bdf03feb82c57524 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-12-11T19:36:52Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-006fe6f501744c09bdf03feb82c575242022-12-22T00:53:08ZengMDPI AGMathematics2227-73902018-04-01646110.3390/math6040061math6040061A Developed Artificial Bee Colony Algorithm Based on Cloud ModelYe Jin0Yuehong Sun1Hongjiao Ma2School of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, ChinaSchool of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, ChinaSchool of Mathematical Sciences, Nanjing Normal University, Nanjing 210023, ChinaThe Artificial Bee Colony (ABC) algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.http://www.mdpi.com/2227-7390/6/4/61artificial bee colony algorithm (ABC)cloud modelnormal cloud modelY conditional cloud generatorglobal optimum |
| spellingShingle | Ye Jin Yuehong Sun Hongjiao Ma A Developed Artificial Bee Colony Algorithm Based on Cloud Model Mathematics artificial bee colony algorithm (ABC) cloud model normal cloud model Y conditional cloud generator global optimum |
| title | A Developed Artificial Bee Colony Algorithm Based on Cloud Model |
| title_full | A Developed Artificial Bee Colony Algorithm Based on Cloud Model |
| title_fullStr | A Developed Artificial Bee Colony Algorithm Based on Cloud Model |
| title_full_unstemmed | A Developed Artificial Bee Colony Algorithm Based on Cloud Model |
| title_short | A Developed Artificial Bee Colony Algorithm Based on Cloud Model |
| title_sort | developed artificial bee colony algorithm based on cloud model |
| topic | artificial bee colony algorithm (ABC) cloud model normal cloud model Y conditional cloud generator global optimum |
| url | http://www.mdpi.com/2227-7390/6/4/61 |
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