Self-adaptive bare-bones differential evolution based on bi-mutation strategy
Bare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-08-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017051/ |
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| author | Hui-yu LIU Ji-hong HAN Lin YUAN Bo YU |
| author_facet | Hui-yu LIU Ji-hong HAN Lin YUAN Bo YU |
| author_sort | Hui-yu LIU |
| collection | DOAJ |
| description | Bare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their differences during evo1ution process，meanwhi1e it may suffer from premature convergence.To overcome these drawbacks，a modified a1gorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individua1 to choose a preferab1e mutation strategy at each mutation operation was introduced，avoiding the evo1ution b1indness brought by the random se1ection of mutation strategy.To retain the a1most parameter-free characteristic of bare-bones a1gorithm，the tuning of choice factor to be adapted was invo1ved in the individua1 evo1ution，inspired by the concept of se1f-adaptive DE.The a1gorithm a1so inc1uded a we11-designed stagnation perturbation mechanism to reduce the risk of trapping into the 1oca1 optima1.Experimenta1 resu1ts on 18 benchmark functions show that the proposed a1gorithm genera11y achieves better performance than state-of-the-art BBDE variants and severa1 we11-known DE a1gorithms in terms of convergence and robustness. |
| format | Article |
| id | doaj-art-1c2577fd59f147d581144c9ff0382858 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1c2577fd59f147d581144c9ff03828582025-01-14T07:12:52ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-08-013820121259711809Self-adaptive bare-bones differential evolution based on bi-mutation strategyHui-yu LIUJi-hong HANLin YUANBo YUBare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their differences during evo1ution process，meanwhi1e it may suffer from premature convergence.To overcome these drawbacks，a modified a1gorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individua1 to choose a preferab1e mutation strategy at each mutation operation was introduced，avoiding the evo1ution b1indness brought by the random se1ection of mutation strategy.To retain the a1most parameter-free characteristic of bare-bones a1gorithm，the tuning of choice factor to be adapted was invo1ved in the individua1 evo1ution，inspired by the concept of se1f-adaptive DE.The a1gorithm a1so inc1uded a we11-designed stagnation perturbation mechanism to reduce the risk of trapping into the 1oca1 optima1.Experimenta1 resu1ts on 18 benchmark functions show that the proposed a1gorithm genera11y achieves better performance than state-of-the-art BBDE variants and severa1 we11-known DE a1gorithms in terms of convergence and robustness.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017051/differentia1 evo1utionbare-bones a1gorithmbi-mutation strategyse1f-adaptive |
| spellingShingle | Hui-yu LIU Ji-hong HAN Lin YUAN Bo YU Self-adaptive bare-bones differential evolution based on bi-mutation strategy Tongxin xuebao differentia1 evo1ution bare-bones a1gorithm bi-mutation strategy se1f-adaptive |
| title | Self-adaptive bare-bones differential evolution based on bi-mutation strategy |
| title_full | Self-adaptive bare-bones differential evolution based on bi-mutation strategy |
| title_fullStr | Self-adaptive bare-bones differential evolution based on bi-mutation strategy |
| title_full_unstemmed | Self-adaptive bare-bones differential evolution based on bi-mutation strategy |
| title_short | Self-adaptive bare-bones differential evolution based on bi-mutation strategy |
| title_sort | self adaptive bare bones differential evolution based on bi mutation strategy |
| topic | differentia1 evo1ution bare-bones a1gorithm bi-mutation strategy se1f-adaptive |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017051/ |
| work_keys_str_mv | AT huiyuliu selfadaptivebarebonesdifferentialevolutionbasedonbimutationstrategy AT jihonghan selfadaptivebarebonesdifferentialevolutionbasedonbimutationstrategy AT linyuan selfadaptivebarebonesdifferentialevolutionbasedonbimutationstrategy AT boyu selfadaptivebarebonesdifferentialevolutionbasedonbimutationstrategy |