| 差异演化的实验研究 |
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| 引用本文： | 谢晓锋,张文俊,张国瑞,杨之廉.差异演化的实验研究[J].控制与决策,2004,19(1):49-52. |
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| 作者姓名： | 谢晓锋 张文俊 张国瑞 杨之廉 |
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| 作者单位： | 1. 清华大学,微电子学研究所,北京,100084
2. 沈阳化工有限公司,辽宁,沈阳,110026 |
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| 摘 要： | 首先基于一些实例研究了差异演化(DE)的参数选择问题；然后在分析DE特点的基础上，将缩放因子F由固定数值设为随机函数，实现了一个简化的DE版本(SDE)，该方法不仅减少了需调整的参数，而且对CR的参数选择更为宽松．与已有文献中遗传算法的带约束型数值优化问题的实验结果对比，表明SDE能在较少的计算次数内获得较好的结果。
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| 关 键 词： | 差异演化 演化计算 数值优化 计算机算法 参数设置 |
| 文章编号： | 1001-0920(2004)01-0049-04 |
Empirical study of differential evolution |
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| XIE Xiao-feng,ZHANG Wen-jun,ZHANG Guo-rui,YANG Zhi-lian.Empirical study of differential evolution[J].Control and Decision,2004,19(1):49-52. |
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| Authors: | XIE Xiao-feng ZHANG Wen-jun ZHANG Guo-rui YANG Zhi-lian |
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| Affiliation: | XIE Xiao-feng~1,ZHANG Wen-jun~1,ZHANG Guo-rui~2,YANG Zhi-lian~1 |
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| Abstract: | The parameters selection of differential evolution (DE) is studied by experiments on some benchmark examples. Then a simplified DE version (SDE) is realized with randomized scaling factor F based on the analysis for the features of DE, which not only reduces a parameter that need to is adjusted, but also is flexible for the selection of parameter CR. The experiments by comparing with genetic algorithm (GA) on some constrained numerical optimization problems show that SDE can get better results in much less evaluation times. |
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| Keywords: | differential evolution evolutionary computation numerical optimization |
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