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论文:2016,Vol:34,Issue(3):411-417 |
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引用本文： |
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何小龙, 白俊强, 李宇飞. 基于全局灵敏度分析的改进微分进化算法[J]. 西北工业大学学报 |
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He Xiaolong, Bai Junqiang, Li Yufei. A Global Sensitivity Analysis Enhanced Differential Evolution Algorithm[J]. Northwestern polytechnical university |
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| 基于全局灵敏度分析的改进微分进化算法 |
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| 何小龙, 白俊强, 李宇飞 |
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| 西北工业大学 航空学院, 陕西 西安 710072 |
| 摘要: |
| 为了提高微分进化算法在问题维度较高、计算量有限的情况下的寻优能力,提出了基于全局灵敏度分析方法的改进微分进化算法。使用Morris-One-at-a-Time (MOAT)全局灵敏度方法对典型函数进行灵敏度分析,与另一种全局灵敏度分析方法Sobol方法进行了对比,证明MOAT方法计算效率和精度较高。基于MOAT方法分别构造了考虑灵敏度信息的改进交叉算子和变异算子,从而得到2种改进微分进化算法GSADE1和GSADE2。使用5个显式50维测试函数对2种改进算法进行了测试,并与基准微分进化算法进行了对比,发现2种改进算法在收敛速度和鲁棒性方面都有所提高。 |
| 关键词:
算法
全局优化
微分进化
计算机仿真
灵敏度分析
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| A Global Sensitivity Analysis Enhanced Differential Evolution Algorithm |
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| He Xiaolong, Bai Junqiang, Li Yufei |
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| College of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| An improved differential evolution (DE) algorithm based on global sensitivity analysis is proposed to enhance performance in high dimension problems with limited computation resources. Morris-One-at-a-Time(MOAT) method was firstly tested on a typical function and compared with Sobol sensitivity method, showing high efficiency and acceptable result. Then MOAT method is used to calculate sensitivity for each dimension of input vector, and new crossover and mutation operators are proposed to incorporate sensitivity for two improved algorithm GSADE1 and GSADE2. Five 50-dimension functions were used for test, showing both two new algorithms are better than the original DE. |
| Key words:
algorithm
global optimization
differential evolution
computer simulation
sensitivity analysis
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| 收稿日期: 2015-10-22
修回日期:
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| DOI: |
| 基金项目: 国家"973"计划(2014CB744804)资助 |
| 通讯作者:
Email： |
| 作者简介: 何小龙(1989—),西北工业大学博士研究生,主要从事飞行器气动外形优化设计及优化方法研究。
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