| 带有自适应变异和指数递增交叉算子的差分进化算法 |
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| 引用本文： | 刘俊梅,高岳林.带有自适应变异和指数递增交叉算子的差分进化算法[J].河南师范大学学报(自然科学版),2009,37(6). |
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| 作者姓名： | 刘俊梅 高岳林 |
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| 作者单位： | 北方民族大学,信息与系统科学研究所,银川,750021 |
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| 基金项目： | 国家自然科学基金，国家社会科学基金，宁夏自然科学基金 |
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| 摘 要： | 针对基本差分进化算法的缺陷,融入指数递增交叉算子以增加算法的收敛速度.当算法陷入早熟后,对最优个体和随机选取的个体采用随机扰动的变异策略,帮助其跳出局部极值.数值仿真实验表明,该算法的收敛速度和精度都明显优于仅带有指数递增交叉算子的差分进化算法和仅带有随机扰动变异策略的差分进化算法.
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| 关 键 词： | 差分进化 指数递增交叉算子 自适应变异 |
Differential Evolution Algorithm with Adaptive Mutation and Index Increased Crossover Operator |
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| LIU Jun-mei,GAO Yue-lin.Differential Evolution Algorithm with Adaptive Mutation and Index Increased Crossover Operator[J].Journal of Henan Normal University(Natural Science),2009,37(6). |
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| Authors: | LIU Jun-mei GAO Yue-lin |
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| Abstract: | For the basic differential evolutionary algorithm's drawback,merging exponent increased crossover operator improves convergence rate.After algorithm fall into premature,the best individual and randomly selecting individuals are mutated by random disturbance strategy to escape local extremes.Numerical simulations show that the proposed algorithm is better than the DE algorithm only with exponent increased crossover operator or the DE algorithm only with random disturbance mutation strategy in convergence rate and accuracy. |
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| Keywords: | differential evolution index increased crossover adaptive mutation |
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