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基于均匀设计的多目标自适应遗传算法及应用
引用本文:赵曙光,焦李成,王宇平,杨万海.基于均匀设计的多目标自适应遗传算法及应用[J].电子学报,2004,32(10):1723-1725.
作者姓名:赵曙光  焦李成  王宇平  杨万海
作者单位:1. 西安电子科技大学电子工程学院,陕西西安 710071;2. 西安电子科技大学应用数学系,陕西西安 710071
摘    要:提出一种多目标遗传算法,将均匀设计技术应用于适应度函数合成和交叉算子构造,以提高遗传算法的空间搜索均匀性、子代质量和运算效率.分析和实验结果表明,该方法可缩短算法运行时间和得到分布较均匀的Pareto有效解集;配合基于元件标称值的网表级高效编码方案和考虑基因位差异的遗传概率调整策略,可实现模拟电路自动设计,通过单次运行即获得对应不同偏好的多种实用化设计结果.

关 键 词:多目标优化  自适应遗传算法  电路进化设计  可进化硬件  均匀设计  
文章编号:0372-2112(2004)10-1723-03
收稿时间:2003-08-10

Uniform Design Based Multi-Objective Adaptive Genetic Algorithm and its Application in Evolutionary Design of Analog Circuits
ZHAO Shu-guang,JIAO Li-cheng,WANG Yu-ping,YANG Wan-hai.Uniform Design Based Multi-Objective Adaptive Genetic Algorithm and its Application in Evolutionary Design of Analog Circuits[J].Acta Electronica Sinica,2004,32(10):1723-1725.
Authors:ZHAO Shu-guang  JIAO Li-cheng  WANG Yu-ping  YANG Wan-hai
Institution:1. School of Electronic Engineering,Xidian University,Xi'an,Shaanxi 710071,China;2. Department of Applied Mathematics,Xidian University,Xi'an,Shaanxi 710071,China
Abstract:In this paper we propose a novel multi-objective genetic algorithm based on the Uniform Design Techniques (UDT),which features a fitness function construction approach using the UDT to obtain a set of uniformly scattered search directions toward the Pareto frontier,and a multi-parents crossover operator using the UDT to improve the quality of offspring and decrease the computation cost.It is proved by experimental results that the method proposed is capable of bringing out more uniformly scattered Pareto optimal solutions within a shorter execution time,and that when combined with an efficient representation scheme of circuits based on standard industrial values of components and a genetic parameters adaptation technique which takes into account loci' different effects and tracks the development of evolution and individuals' diversity,it can be expected to realize automated design of analog circuits and to provide a set of effective results via a single execution.
Keywords:multi-objective optimization  adaptive genetic algorithm  evolutionary circuit design  evolvable hardware  uniform design
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