| 基于反思的思维进化算法 |
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| 引用本文： | 郭红戈,谢克明.基于反思的思维进化算法[J].太原理工大学学报,2011,42(3):232-234. |
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| 作者姓名： | 郭红戈 谢克明 |
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| 作者单位： | 1. 太原理工大学信息工程学院,太原030024;太原科技大学电子信息工程学院,太原030024
2. 太原理工大学信息工程学院,太原,030024 |
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| 摘 要： | 针对思维进化算法(MEA)群体多样性少,易陷入局部极值的问题,提出了能够学习并进行反思的思维进化算法,同时分析了该算法的机制。设计利用子群体的线性组合实现信息共享,通过适应度值的比较进行反思,运用进化历史最优值控制异化策略,提高了搜索速度,保证了种群的多样性,使得收敛速度和全局收敛性均达到较好平衡。测试函数寻优验证了算法的可行性和高效性。
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| 关 键 词： | 思维进化算法 学习 反思 历史最优值 |
MEA Design Based on Consideration |
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| GUO Hong-ge,XIE Ke-ming.MEA Design Based on Consideration[J].Journal of Taiyuan University of Technology,2011,42(3):232-234. |
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| Authors: | GUO Hong-ge XIE Ke-ming |
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| Institution: | GUO Hong-ge1,2,XIE Ke-ming1(1.College of Information Engineering,TUT,Taiyuan 030024,China,2.College of Electronic and Information Engineering,Taiyuan University of Science and Technology,China) |
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| Abstract: | In order to add population diversity,mind evolutionary algorithm(MEA) based on consideration was presented.The linear combination of subpopulation was used to realize social information share,and fitness comparing was used consideration.Dissimilation strategy with density control was designed according to history classic individual.The improved algorithm realized optimization process by total optimal characteristics of the whole population,and achieved the best balance between searching velocity and global ... |
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| Keywords: | mind evolutionary algorithm study consideration history classic individual |
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