基于置信区间的约束多精度序贯代理模型优化方法及应用  

Multi-fidelity sequential constraint updating optimization approach based on confidence intervals and its application

作　　者：钱家昌[1,2] 程远胜[1] 张锦岚[2] QIAN Jiachang;CHENG Yuansheng;ZHANG Jinlan(School of Naval Architecture and Ocean Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;Wuhan Second Ship Design and Research Institute,Wuhan 430205,China)

机构地区：[1]华中科技大学船舶与海洋工程学院,湖北武汉430074 [2]武汉第二船舶设计研究所,湖北武汉430205

出　　处：《中国舰船研究》2021年第4期37-43,共7页Chinese Journal of Ship Research

基　　金：国防科技工业海洋防务技术创新中心创新基金资助项目(YT19201701)。

摘　　要：[目的]水下结构物优化设计领域面临着仿真耗时优化的难题。针对目标不耗时、约束耗时这类优化问题,开展多精度数据来源情况下的约束序贯代理模型优化方法研究。[方法]提出一种基于置信区间的约束多精度序贯Co-Kriging代理模型优化方法(MF-SCU-CI),建立能综合评估代理模型不确定性水平、高/低精度模型相关程度以及成本系数的Co-H函数,用于指导序贯优化过程。然后,通过3个典型的数值测试函数和纵横加筋圆锥壳结构振动优化工程案例进行应用研究。[结果]结果表明,所提出的MF-SCUCI方法较基于置信区间的约束单精度序贯代理模型优化方法(SCU-CI)具有更优的可行性比率,且优化求解效率更高,能够进一步减少耗时的仿真次数。[结论]该方法适用性好,具有良好的工程应用前景。[Objectives]This study addresses the problem of time-consuming simulation in the optimization design of underwater structures.Focusing on time-consuming and non-time-consuming targets and constraints,it proposes an optimization method for constrained sequential surrogate models in the case of multi-fidelity data sources.[Methods]A multi-fidelity sequential constraint updating optimization approach based on confidence intervals and the Co-Kriging surrogate model(MF-SCU-CI)is proposed.The Co-H function is established to take into consideration the uncertainty of the surrogate model and the correlation degree and time consumption ratio of the high/low fidelity model.Three typical numerical test functions and an engineering example of longitudinal and transverse stiffened conical shell structure for vibration optimization are then tested.[Results]The results demonstrate that the feasibility ratio and effectiveness of the MF-SCU-CI method are better than those of the existing SCU-CI method.In addition,the MF-SCU-CI method can further reduce the number of simulation runs.[Conclusions]The proposed MF-SCU-CI method shows great potential for practical simulation-based engineering design optimization.

关 键 词：代理模型 CO-KRIGING 多精度 置信区间 序贯约束更新优化 

分 类 号：U662.2[交通运输工程—船舶及航道工程]