| 基于混合加点准则的代理模型优化设计方法 |
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| 引用本文： | 李正良,彭思思,王涛.基于混合加点准则的代理模型优化设计方法[J].工程力学,2022,39(1):27-33. |
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| 作者姓名： | 李正良 彭思思 王涛 |
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| 作者单位： | 1.重庆大学土木工程学院，重庆 400045 |
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| 基金项目： | 国家自然科学基金项目(51478064)%国家自然科学基金国际(地区)合作与交流项目(51611140123) |
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| 摘 要： | 在工程优化设计中,采用数值仿真模拟计算结构响应需耗费大量的时间和计算成本,给计算密集型的优化设计带来了巨大挑战,因此基于代理模型的序列优化设计方法得到了深入研究和广泛应用.对代理模型的序列优化方法框架进行了简要的概述;针对现有方法中存在的不足,发展了一类模型无关的混合加点准则,使优化循环过程中产生的新样本点分布在当前最...
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| 关 键 词： | 代理模型 序列优化 混合加点准则 全局搜索 交叉验证 |
| 收稿时间： | 2020-12-22 |
A SURROGATE-BASED OPTIMIZATION DESIGN METHOD BASED ON HYBRID INFILL SAMPLING CRITERION |
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| LI Zheng-liang,PENG Si-si,WANG Tao.A SURROGATE-BASED OPTIMIZATION DESIGN METHOD BASED ON HYBRID INFILL SAMPLING CRITERION[J].Engineering Mechanics,2022,39(1):27-33. |
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| Authors: | LI Zheng-liang PENG Si-si WANG Tao |
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| Affiliation: | 1.School of Civil Engineering, Chongqing University, Chongqing 400045, China2.Key Laboratory of New Technology for Construction of Cities in Mountain Area (Chongqing University), Ministry of Education, Chongqing 400045, China |
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| Abstract: | In engineering optimization design, numerical simulation calculation of structural response is expensive and time-consuming, which brings great challenges to compute-intensive optimization design. Therefore, the surrogate-based sequential optimization method has been well studied and widely used. Firstly, the framework of the surrogate-based sequence optimization is summarized at first. Secondly, a model-independent hybrid infill sampling criterion is developed in view of the insufficiency in existing methods. The new sample points generated during optimization process are distributed in the neighborhood of the current minimum value and the region with largest cross-validation error in the design space. The local exploitation and global exploration can be carried out simultaneously to find accurate global optimal solution. Thirdly, hybrid infill sampling criterion is introduced into the surrogate-based optimization framework combined with particle swarm optimization algorithm, and an efficient surrogate-based optimization design method is proposed. Finally, the proposed method is verified by mathematical and engineering examples. Compared with the optimization method by the grounds of traditional criterions, the proposed method can keep the tradeoff of accuracy and efficiency, which has better global optimization characteristics. |
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| Keywords: | surrogate model sequential optimization hybrid infill sampling criterion global exploration cross-validation |
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