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论文:2021,Vol:39,Issue(2):292-301 |
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引用本文： |
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叶鹏程, 王聪聪, 潘光. 一种基于多层设计空间缩减策略的近似高维优化方法[J]. 西北工业大学学报 |
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YE Pengcheng, WANG Congcong, PAN Guang. An approximate high-dimensional optimization method using hierarchical design space reduction strategy[J]. Northwestern polytechnical university |
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| 一种基于多层设计空间缩减策略的近似高维优化方法 |
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| 叶鹏程1,2, 王聪聪3, 潘光1,2 |
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1. 西北工业大学 航海学院, 陕西 西安 710072;
2. 西北工业大学 无人水下运载技术重点实验室, 陕西 西安 710072;
3. 中国航空工业集团公司 洛阳电光设备研究所, 河南 洛阳 471000 |
| 摘要: |
| 针对高维昂贵黑箱问题（high-dimensional expensive black-box，HEB）处理过程中工程模型复杂、计算量大的难题，提出一种基于多层设计空间缩减策略的近似高维优化方法（hierarchical design space reduction strategy based approximate high-dimensional optimization method，HSRAHO）。利用3种经典代理模型：多项式响应面模型、径向基函数模型和克里金模型，使用基于预测均方根误差权重因子优化方法计算获得各代理模型权系数，通过加权叠加构建组合代理模型，替代实际高维黑箱模型。使用多层设计空间缩减策略根据已知信息确定设计子空间，并在其内部确定有效样本点，逐步提高组合代理模型在感兴趣区域的预测精度，直至优化收敛。将提出的近似高维优化方法HSRAHO应用于标准优化函数和翼型设计优化问题，测试结果验证了该方法在高维优化效率和全局收敛性方面的优势。 |
| 关键词:
高维昂贵黑箱问题
高维优化
多层设计空间缩减策略
组合代理模型
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| An approximate high-dimensional optimization method using hierarchical design space reduction strategy |
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| YE Pengcheng1,2, WANG Congcong3, PAN Guang1,2 |
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1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China;
2. Key Laboratory for Unmanned Underwater Vehicle, Northwestern Polytechnical University, Xi'an 710072, China;
3. Luoyang Institute of Electro-Optical Equipment, AVIC, Luoyang 471000, China |
| Abstract: |
| To overcome the complicated engineering model and huge computational cost, a hierarchical design space reduction strategy based approximate high-dimensional optimization(HSRAHO) method is proposed to deal with the high-dimensional expensive black-box problems. Three classical surrogate models including polynomial response surfaces, radial basis functions and Kriging are selected as the component surrogate models. The ensemble of surrogates is constructed using the optimized weight factors selection method based on the prediction sum of squares and employed to replace the real high-dimensional black-box models. The hierarchical design space reduction strategy is used to identify the design subspaces according to the known information. And, the new promising sample points are generated in the design subspaces. Thus, the prediction accuracy of ensemble of surrogates in these interesting sub-regions can be gradually improved until the optimization convergence. Testing using several benchmark optimization functions and an airfoil design optimization problem, the newly proposed approximate high-dimensional optimization method HSRAHO shows improved capability in high-dimensional optimization efficiency and identifying the global optimum. |
| Key words:
high-dimensional expensive black-box problems
high-dimensional optimization
hierarchical design space reduction strategy
ensemble of surrogates
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| 收稿日期: 2020-05-14
修回日期:
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| DOI: 10.1051/jnwpu/20213920292 |
| 基金项目: 国家自然科学基金（61803306）、中国博士后科学基金面上项目（2019M660264）与中央高校基本科研业务费专项资金（3102019HHZY03009）资助 |
| 通讯作者:
Email： |
| 作者简介: 叶鹏程(1991-),西北工业大学助理研究员、博士,主要从事近似高维优化方法与水下航行器设计研究。
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| 作者相关文章 |
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| 叶鹏程 在本刊中的所有文章 |
| 王聪聪 在本刊中的所有文章 |
| 潘光 在本刊中的所有文章 |
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