基于降维扫描方法的自适应多目标遗传算法

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (18): 78-81.

基于降维扫描方法的自适应多目标遗传算法

王晓兰,田宏亮,王慧中,杨琳琳

兰州理工大学电气工程与信息工程学院,兰州 730050

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-06-21 发布日期:2007-06-21
通讯作者: 王晓兰

Adaptive multi-objective genetic algorithm based on dimension reduction and scanning approach

WANG Xiao-lan,TIAN Hong-liang,WANG Hui-zhong,YANG Lin-lin

College of Electrical Engineering and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China

Received:1900-01-01 Revised:1900-01-01 Online:2007-06-21 Published:2007-06-21
Contact: WANG Xiao-lan

摘要/Abstract

摘要： 为了有效地应用遗传算法解决H2/H∞鲁棒控制系统设计问题,将遗传算法与局部优化方法相结合,提出了基于降维扫描方法的自适应多目标遗传算法（DRSA-MOGA）。通过引入适应度函数标准化方法、基于最优Pareto解集搜索的降维扫描方法和适应度函数自适应调整方法,提高了算法的全局优化性能和局部搜索能力。仿真结果表明,DRSA-MOGA算法在不损失解的均匀度的情况下可以达到很高的逼近度。

Abstract: Combining genetic algorithm with local search,adaptive Multi-Objective Genetic Algorithm based on the Dimension Reduction and Scanning Approach（DRSA-MOGA） is introduced in order to make multi-objective robust control system smoothly reach H2/H∞ objective optimal solutions. By introducing three methods that are the method of fitness function normalization,the dimension reduction and scanning method and the adaptive adjust method of fitness function,the performance of global optimization and the ability of local search are improved. Simulation results show that Pareto solutions obtained by applying DRSA-MOGA can achieve a very high approximation,and can meanwhile keep good diversity.

王晓兰,田宏亮,王慧中,杨琳琳. 基于降维扫描方法的自适应多目标遗传算法[J]. 计算机工程与应用, 2007, 43(18): 78-81.

WANG Xiao-lan,TIAN Hong-liang,WANG Hui-zhong,YANG Lin-lin. Adaptive multi-objective genetic algorithm based on dimension reduction and scanning approach[J]. Computer Engineering and Applications, 2007, 43(18): 78-81.