龙周，陈松坤，王德禹

上海交通大学 海洋工程国家重点实验室； 高新船舶与深海开发装备协同创新中心， 上海 200240

出版日期:2019-01-28发布日期:2019-01-28
通讯作者:王德禹，男，教授，博士生导师，电话（Tel.）：021-62933131；E-mail: dywang@sjtu.edu.cn.
作者简介:龙周（1994-），女，湖南省长沙市人，硕士生，主要研究方向为船舶结构强度与优化.
基金资助:工信部高技术船舶科研项目 (［2016］548)，教育部财政部重大专项（201335)

Reliability-Based Design Optimization of Ship Structures Based on SMOTE Algorithm

LONG Zhou,CHEN Songkun,WANG Deyu

State Key Laboratory of Ocean Engineering; Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration, Shanghai Jiao Tong University, Shanghai 200240, China

Online:2019-01-28Published:2019-01-28

摘要/Abstract

摘要： 针对常规船舶结构可靠性优化设计由高度非线性带来的计算效率低、收敛困难的问题，提出了基于SMOTE (Synthetic Minority Oversampling Technique)算法的船舶结构可靠性优化设计方法.利用SMOTE算法建立了改进的BP (Back Propagation)神经网络模型，以较少的样本点完成了极限状态函数的高度近似，克服了以往代理模型不能同时满足精度和效率要求的缺点，并通过数学算例验证了使用SMOTE算法建立BP神经网络模型的可行性和有效性.将改进的BP神经网络模型和模拟退火法嵌入单循环优化策略，并将其用于船舶舱段的可靠性优化设计，验证了所提出的可靠性优化设计方法的求解效率和精度，为大型工程结构的可靠性优化设计提供了思路.
关键词: 可靠性优化设计, 极限状态函数, 单循环优化策略, SMOTE算法
Abstract: Aimed at the problem that ship structures reliability-based design optimization has poor efficiency and difficult convergence due to high nonlinearity, a reliability-based design optimization of ship structures based on SMOTE (synthetic minority oversampling technique) algorithm is proposed. The innovation is to establish an improved BP (back propagation) neural network by SMOTE algorithm and the limit state function with high approximation could be set up with fewer samples, which overcomes the shortcoming that old model cannot satisfy both accuracy and efficiency requirements. Moreover, the feasibility of establishing BP neural network model by SMOTE algorithm has been proved by a mathematical instance. Then put the improved BP neural network and simulate anneal arithmetic into single loop approach optimized strategy to solve the issue of ship structure reliability-based design optimization. The result confirms the efficiency and accuracy of the model. In addition, the proposed model can provide an idea for large engineering structures reliability-based design optimization.
Key words: reliability-based design optimization, limit state function, single loop approach, SMOTE (synthetic minority oversampling technique) algorithm


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