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基于差异演化算法和多属性决策的机电系统可靠性多目标优化设计
引用本文:卢青波,张学良,温淑花,兰国生,刘丽琴.基于差异演化算法和多属性决策的机电系统可靠性多目标优化设计[J].工程设计学报,2011,18(6):412-417.
作者姓名:卢青波  张学良  温淑花  兰国生  刘丽琴
作者单位:1. 太原科技大学 机电工程学院,山西 太原 030024;2. 郑州职业技术学院,河南 郑州 450121
基金项目:国家自然科学基金资助项目(50775153);高等学校博士学科点专项科研基金资助项目(20091415110002);山西省自然科学基金资助项目(2008011027-1);山西省研究生教育改革研究项目(20092016);山西省研究生优秀创新项目(20093022)
摘    要:针对机电系统可靠性设计问题,以可靠性和费用(或体积等)最优为目标建立可靠性设计的多目标优化模型.提出了自适应多目标差异演化算法,该算法提出了自适应缩放因子和混沌交叉率,采用改进的快速排序方法构造Pareto最优解,采用NSGA-II的拥挤操作对档案文件进行消减.采用自适应多目标差异演化算法获得多目标问题的Pareto最优解,利用TOPSIS方法对Pareto最优解进行多属性决策.实际工程结果表明:自适应多目标差异演化算法调节参数更少,且求得的Pareto最优解分布均匀;采用基于TOPSIS的多属性决策方法得到的结果合理可行.

关 键 词:可靠性  多目标优化  多属性决策  TOPSIS  自适应  
收稿时间:2011-12-28

Mechanical electronics system reliability multi-objective optimization design based on differential evolution algorithm and multiple attribute decision making
LU Qing-bo,ZHANG Xue-liang,WEN Shu-hua,LAN Guo-sheng,LIU Li-qin.Mechanical electronics system reliability multi-objective optimization design based on differential evolution algorithm and multiple attribute decision making[J].Journal of Engineering Design,2011,18(6):412-417.
Authors:LU Qing-bo  ZHANG Xue-liang  WEN Shu-hua  LAN Guo-sheng  LIU Li-qin
Affiliation:1(1.College of Mechanical Electronic Engineering,Taiyuan University of Science and Technology, Taiyuan 030024,China;2.Zhengzhou Technical College,Zhengzhou 450121,China)
Abstract:In order to improve mechanical electronics system reliability, a multi-objective optimization model based on reliability indices and cost (volume et al.) was constructed. Adaptive Multi-Objective Differential Evolution Algorithm (AMODE) was proposed. The algorithm proposed chaotic crossover ratio and adaptive scaling factor, improved quick sort algorithm was employed to build Pareto optimal solutions, and the shrink of an external archive was achieved based on crowding distance, which was used in NSGA-II. The Pareto optimal solutions were obtained by AMODE. Multiple attribute decision making method TOPSIS was adopted to rank these solutions. An actual project solution shows that less parameters of AMODE need adjust and the algorithm can obtain uniformly distributed Pareto optimal solutions. The result based on multiple attribute decision making method-TOPSIS is reasonable and feasible.
Keywords:reliability  multi-objective optimization  multiple attribute decision making  TOPSIS  adaptive
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