基于灰色粒子群算法的可靠性稳健优化设计  

Robust optimization design for reliability based on grey particle swarm algorithm

作　　者：刘仁云[1] 张义民[2] 于繁华[3] 

机构地区：[1]吉林大学机械科学与工程学院,长春130022 [2]东北大学机械工程与自动化学院,沈阳110004 [3]长春师范学院数学学院,长春130032

出　　处：《吉林大学学报（工学版）》2006年第6期893-897,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金资助项目(50175043)

摘　　要：为提高车辆零部件的安全性和稳健性,应用可靠性稳健优化设计理论和多目标决策方法,将车辆前轴的可靠性稳健优化设计转化为多目标优化问题。运用灰色理论中的关联分析法,选取粒子群算法中的全局极值和个体极值,提出了适合可靠性稳健优化设计中多目标模型求解的灰色粒子群算法。与传统方法相比,该方法更能迅速准确地得到车辆前轴的可靠性稳健优化设计信息。To improve the safety and robustness of automobile components, the reliability robust optimization theory and multi-objective decision making methods are proposed for automobile front-axle to change the reliability robust optimization problem into the multi-objective optimization problem. And the global best and personal best of particle swarm algorithm are selected by the grey relevancy theory. Further more, the grey particle swarm algorithm is presented for muhi-objective models solution in the reliability robust optimization design. Comparing with traditional methods, the reliability robust optimization design information of automobile front-axle can be obtained accurately and quickly by the proposed method.

关 键 词：机械设计 稳健优化设计 灰色粒子群算法 随机摄动法 多目标优化 

分 类 号：TH123[机械工程—机械设计及理论]