| 多变异策略的自适应差分演化算法 |
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| 引用本文： | 周雅兰,徐 志.多变异策略的自适应差分演化算法[J].计算机科学,2015,42(6):247-250, 255. |
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| 作者姓名： | 周雅兰 徐 志 |
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| 作者单位： | 1. 广东财经大学信息学院 广州510320
2. 中山大学信息科学与技术学院 广州510006 |
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| 基金项目： | 本文受广州市珠江科技新星专项(2012J2200085),广东省教育厅高校优秀青年创新人才培育项目(2012LYM_0066),广东商学院科研创新团队建设计划资助 |
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| 摘 要： | 差分演化(Differential Evolution,DE)算法的性能依赖于变异策略的选择和控制参数的设置.不同问题对DE的变异策略和参数的设置各不相同.为了提高DE的性能,提出一种多变异策略的自适应差分演化算法,建立由多种变异策略组成的策略池,两个主要参数自适应策略控制.为了验证所提算法的性能,在测试数据集CEC2013上进行了实验,并将其与使用6种不同变异策略的原始DE和4种改进DE进行比较.实验结果表明,提出的算法是一种有效的DE变种,其性能优于其它DE.
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| 关 键 词： | 差分演化算法 多变异策略 参数自适应 |
Self-adaptive Differential Evolution with Multi-mutation Strategies |
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| ZHOU Ya-lan and XU Zhi.Self-adaptive Differential Evolution with Multi-mutation Strategies[J].Computer Science,2015,42(6):247-250, 255. |
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| Authors: | ZHOU Ya-lan and XU Zhi |
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| Affiliation: | School of Information Science,Guangdong University of Finance & Economics,Guangzhou 510320,China and School of Information Science and Technology,Sun Yat-sen University,Guangzhou 510006,China |
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| Abstract: | The performance of differential evolution(DE) algorithm often depends heavily on the mutation strategy and control parameters.A novel self-adaptive differential evolution with multi-mutation strategies called SMSDE was proposed.SMSDE designs a strategy pool consisting of many kinds of mutation strategy and applies self-adaptive strategies to two main parameters.In order to verify the performance of SMSDE,SMSDE was compared with 6 original DEs and 4 advanced DEs on CEC2013 benchmark functions.The experimental results show that SMSDE is superior to original DEs,and is competitive with the current advanced DE variants. |
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| Keywords: | Differential evolution algorithm Multi-mutation strategies Parameter self-adaptation |
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